\r\n\t(i) Quantum dots of very high-quality optical applications, Quantum dot light-emitting diodes (QD-LED) and ‘QD-White LED’, Quantum dot photodetectors (QDPs), Quantum dot solar cells (Photovoltaics).
\r\n
\r\n\t(ii) Quantum Computing (quantum bits or ‘qubits’), (vii) The Future of Quantum Dots (broad range of real-time applications, magnetic quantum dots & graphene quantum dots), Superconducting Loop, Quantum Entanglement, Quantum Fingerprints.
\r\n
\r\n\t(iii) Biomedical and Environmental Applications (to study intracellular processes, tumor targeting, in vivo observation of cell trafficking, diagnostics and cellular imaging at high resolutions), Bioconjugation, Cell Imaging, Photoelectrochemical Immunosensor, Membranes and Bacterial Cells, Resonance Energy-Transfer Processes, Evaluation of Drinking Water Quality, Water and Wastewater Treatment, Pollutant Control.
",isbn:"978-1-80356-594-1",printIsbn:"978-1-80356-593-4",pdfIsbn:"978-1-80356-595-8",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"0dd5611c62c91569bd2819e68852002a",bookSignature:"Prof. Jagannathan Thirumalai",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11756.jpg",keywords:"LED, Organic LEDs, Dyes & Pigments, Solar Cells, Laser Photonics, Electronic Switching Devices, Qubits, Josephson Junction, Bioconjugation, Cell Imaging, Photoelectrochemical Immunosensor, Membranes, and Bacterial Cells",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 16th 2022",dateEndSecondStepPublish:"May 27th 2022",dateEndThirdStepPublish:"July 26th 2022",dateEndFourthStepPublish:"October 14th 2022",dateEndFifthStepPublish:"December 13th 2022",remainingDaysToSecondStep:"6 days",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. J. Thirumalai received his Ph.D. from Alagappa University, Karaikudi, He was also awarded the Post-doctoral Fellowship from Pohang University of Science and Technology (POSTECH), the Republic of Korea. His research interests focus on luminescence, self-assembled nanomaterials, and thin-film optoelectronic devices. He has published more than 60 SCOPUS/ISI indexed papers and 11 book chapters, edited 4 books, and member of several national and international societies like RSC, OSA, etc. His h-index is 19.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"99242",title:"Prof.",name:"Jagannathan",middleName:null,surname:"Thirumalai",slug:"jagannathan-thirumalai",fullName:"Jagannathan Thirumalai",profilePictureURL:"https://mts.intechopen.com/storage/users/99242/images/system/99242.png",biography:"Dr. J. Thirumalai received his Ph.D. from Alagappa University, Karaikudi in 2010. 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1. Introduction
Phonation results from the interaction of the vocal folds with the airflow and the air column above them [1, 2]. When air particles pass through the glottis and their speed increases, this reduces the pressure between the vocal folds triggering a suction effect that brings the vocal folds closer to each other, followed by an elastic recoil that promotes a new glottic adduction, thus enabling the production of voice. The sound that results from the vibration of the vocal folds, which is modified by the resonance cavities, is called voice. This audible sound is the product of a complex relation between the pressure and velocity of expiratory airflow, intensity, the different patterns of abduction and adduction of the vocal folds, the vocal tract configuration and resulting resonances [3].
Voice disorders can have a significant negative impact on a person’s life, because the voice is an important tool for communication [4]. There is a voice perturbation whenever the vocal quality, intensity, fundamental frequency (f0) or vocal flexibility are altered for the age, sex and culture of the speaker ([5], p. 5). Any difficulty or alteration in the vocal emission that prevents the natural production of the voice is called dysphonia. Dysphonia manifests itself through the following changes: Perturbations in vocal quality, emission effort, vocal fatigue, loss of vocal power, uncontrolled variations of fundamental frequency, lack of intensity and projection, loss of vocal efficiency, low vocal resistance and unpleasant sensations during vocal emission. These result in the alteration of one or several acoustic characteristics of the voice.
1.1. Vocal evaluation
Vocal evaluation is considered the first stage of intervention and rehabilitation. Voice assessment has the following main objectives [3]: To know the vocal behaviour of the person, identify the causes of the vocal problem, describe the vocal characteristics of the individual, identify vocal habits, to characterise the relation between body and personality. Perceptual evaluation of voice is routinely used in clinical practice but still poses some inter- and intra-subject problems because it is subjective and often not correlated with the severity of the pathology [6].
According to Chan and Yiu [7], the perceptual evaluation is a subjective process, in which the intra- and inter-rater reliability can vary. Pontes et al. [8] also point out that the perceptual evaluation of vocal quality assumes a subjective character, which varies according to the evaluator, with its internal standards on voice quality, with their perception skills, discrimination and experience with regard to the evaluation of voice. Nevertheless, auditory perception-based assessments can be performed rapidly, are non-invasive, do not require electronic equipment, so results are readily available [9].
Several scales have been proposed for the perceptual evaluation of voice quality [10], but the GRBAS ([11], pp. 181–209; [12], pp. 83–84) and Auditory-Perceptual Evaluation of Voice (CAPE-V) [13–15] are the most widely used [16] and recommended as part of standardised voice evaluation protocols [3, 17–19].
The GRBAS scale ([11], pp. 181–209; [12], pp. 83–84) defines five parameters for vocal quality classification: Grade (G), Rough (R), Breathy (B), Astenic (A), Strain (S). The parameter G corresponds to the grade of alteration of vocal quality; R is psychoacoustic vocal fold vibration irregularity impression, corresponding to the vocal fold vibration irregularity, fluctuation in the value of f0 and amplitude of the sound of the glottal source; the parameter B refers to the psychoacoustic impression of air passage through the glottis, thus relating to turbulence; the parameter A assesses the weakness or lack of energy in the voice, thus characterising a weak intensity of source sound glottic, or lack of harmonics; finally, the S that characterises the state hyperfunction of phonation. The scale is scored from 0 to 3 for each of its five parameters: 0, normal or absence of hoarseness; 1, slight; 2, moderate; 3, severe.
The CAPE-V scale [13–15] uses six features to evaluate voice quality: Overall severity, roughness, breathiness, strain, pitch, loudness. The parameter overall severity captures a global impression of voice disturbance, roughness allows clinicians to register source irregularities, the perception of breathiness results from air escape, and strain is related to the perception of vocal effort. The perceived f0 and intensity are registered as the pitch and loudness parameters, respectively. Comments about resonance and additional features, such as falsetto or tremor, can also be registered. The scale is scored from 0 to 100 on 100-mm Likert scales for each of its six parameters: Mildly Deviant (MI), Moderately Deviant (MO), and Severely Deviant (SE) qualitative attributes are distributed uniformly along the scale, and the consistent (C) and intermittent (I) labels can be associated with each parameter.
The first European Portuguese (EP) translation [20] of the CAPE-V included six new EP sentences designed to elicit the production of every oral vowel in EP, easy onset with/s/, only voiced phonemes, hard glottal attack, nasal phonemes and voiceless stops ([20], p. 971). The proposed new sentences (thoroughly reviewed by a Speech Scientist, a Linguist and three experienced speech and language therapists (SLTs)) and used in its original form in the study reported in this book chapter were: <A Marta e o avô vivem naquele casarão rosa velho> [ɐ ˈmaɾtɐ i u ɐˈvo ˈvivɐ̃j nɐˈkelɨ kɐzɐˈɾɐ̃w ˈʁɔzɐ ˈvɛʎu]; <Sofia saiu cedo da sala> [suˈfiɐ sɐˈiw ˈsedu dɐ ˈsalɐ]; <a asa do avião andava avariada> [ɐ ˈazɐ du ɐviˈɐ̃w ɐ̃ˈdavɐ ɐvɐɾiˈadɐ]; <agora é hora de acabar> [ɐˈɡɔɾɐ ɛ ˈɔɾɐ dɨ ɐkɐˈbaɾ]; <a minha mãe mandou-me embora> [ɐ ˈmiɲɐ mɐ̃j mɐ ̃domɨ ẽˈbɔɾɐ]; <o Tiago comeu quatro peras> [u tiˈaɡu kuˈmew kuˈatɾu ˈpeɾɐʃ].
1.2. Auditory-perceptual training of evaluators
The continuous training of the evaluators is recommended, in order to guarantee the reliability and validity of a perceptual evaluation of voice. Both the intra- and inter-rater reliability may vary because perceptual voice assessment is a subjective process, but it is generally accepted that the inter-rater reliability is a greater concern. Kreiman et al. [21, 22] argued that reliability variation can be attributed to the different internal standards acquired by evaluators.
Helou et al. [23] conducted a study with 10 experienced evaluators and 10 inexperienced evaluators, who rated 10 male voices and 10 female voices with CAPE-V. The results revealed that inexperienced evaluators rate voices more severely than the experienced evaluators. Inexperienced evaluators also had lower intra- and inter-rater reliability than those with experience. Experienced evaluators rated the voices similarly.
Studies by Kreiman et al. [21] and Gerratt et al. [24] used natural voice samples and/or voice samples synthesised as anchors, and showed that inter- and intra-rater reliability in the perceptual assessment of voice improved with training.
Anchors are considered references that listeners (evaluators) can use to compare with the signals they are invited to judge [7]. In the study by Eadie and Smith [25], 20 inexperienced and 20 experienced evaluators rated 20 samples of normal voices. The results of this study showed that the anchors reduce inter-rater variability.
Silva et al. [26] analysed the impact of auditory-perceptual training on the evaluation of voice performed by speech and language therapy students. Seventeen students analysed samples of normal and dysphonic voices with the GRBAS scale. All students had auditory training during a total of nine weekly sessions, each about 15 min long. The evaluation of voice samples was performed before and after the training, and in four other moments during the meetings. Student ratings were compared with an assessment by three voice specialists. The results showed that the students’ success rate at the pre-training moment was considered between regular and good. A maintenance of the number of hits throughout the evaluations performed, for most of the scale parameters, was also observed. Regarding the post-training moment, a better analysis was observed, mainly for the Astenic (A) parameter.
Training judges/listeners has been shown to ‘increase the extent to which they share common standards for different’ ([10], p. 63) voice qualities, so the current study also includes the intra- and inter-rater reliability analysis of the perceptual evaluation of voices with the GRBAS and CAPE-V scales, before and after a training programme.
1.3. Cross-cultural adaptation and translation of the GRBAS and CAPE-V scales
To the best of our knowledge, there are no standard assessment instruments to perceptually evaluate voice quality in EP, so clinicians in Portugal use various translations of GRBAS ([27, 28], pp. 66–69) and CAPE-V [29], and generally have no access to EP versions of the original instructions published by the Japan Society of Logopedics and Phoniatrics ([11], pp. 181–209) or the American Speech-Language-Hearing Association [13]. They therefore use various procedures and non-standardised definitions of the parameters [30–32]. This results in different voice assessment methods hamper the development, objectivity and specificity of therapeutic plans, thus compromising the efficiency and efficacy of intervention strategies.
We believe the access to the original author’s definitions of core concepts behind the development of health instruments, contributes towards the standardisation of evaluations procedures, and considerable improvements in intra- and inter-rater reliability. The translation and adaptation processes of the whole tool (not just the score sheets) should follow international guidelines [33] for cross-cultural adaptation of health assessment instruments. Evidence-based practice would thus be enhanced, and comparisons across countries would be facilitated. A broader evidence base for effective service delivery planning based on results from large-scale randomised controlled trials requires that the same assessment instruments are validated in different cultures.
Cross-cultural adaptation of instruments is necessary when the new target population differs from the original in which the assessment tool is used regarding culture or cultural background, country and language. There are specific guidelines [34, 35] to conserve the sensibility of the assessment tool in the original culture [36]. The steps that must be followed, if relevant to the specific assessment tool, are [37, 38]: translation, synthesis of the translations, back-translation, committee review and pre-testing.
The first stage of a cross-cultural adaptation must be the production of several translations by, at least, two independent translators. In a second stage, the two translators synthesise the results of the translations, producing one common translation [37]. It is then necessary to back-translate the assessment tool (third stage), which means translating back from the final language into the source language, producing as many back-translations as translations, based on the synthesised translation [36]. In the fourth stage, an expert committee compares the source and the final version. The fifth stage consists of a cognitive debriefing that tests alternative wording, understandability, and interpretation of the translation [35].
In this study, the cross-cultural adaptation and translation of the GRBAS and CAPE-V scales to EP were carried out following these international guidelines [33].
2. Method
Ethical approval was obtained from all authorities required by Portuguese bylaws for clinical research: National data protection committee, independent ethics committees. Informed consent was collected from all participants prior to any data collection.
2.1. Cross-cultural adaptation and translation of the GRBAS and CAPE-V scales
The American Speech-Language-Hearing Association (ASHA) Special Interest Division 3 was contacted by the first author of this book chapter, and the ‘Request to Translate & Distribute’ CAPE-V was granted to the University of Aveiro by ASHA on 28 January 2008. The Portuguese version of the CAPE-V has been available from the Advanced Communication and Swallowing Assessment (ACSA) http://acsa.web.ua.pt/platform since 2010.
At a later stage, the same author (Luis M.T. Jesus) contacted the Japan Society of Logopedics and Phoniatrics (JSLP), and the University of Aveiro was granted permission to complete a new translation and adaptation of the GRBAS on the 10 January 2013. Professor Eiji Yumoto, on behalf of the JSLP, concluded that there were no detailed descriptions of the GRBAS scale in other languages besides Japanese, so he generously granted the University of Aveiro access to a detailed description of the GRBAS scale, published in 1979 by the JSLP. This book [11] was written in Japanese, and Professor Minoru Hirano described the scale only briefly in his publication ([12], pp. 83–84).
The work reported in this book chapter reports work that is part of the validation process of a voice evaluation protocol developed by our research team [18–20] and freely available from the ACSA platform. University of Aveiro’s Voice Evaluation Protocol [18] includes the assessment of voice quality, glottal attack, respiratory support, respiratory-phonatary-articulatory coordination, digital laryngeal manipulation (laryngeal crepitation) and laryngeal tension. It also allows the self-assessment of voice quality and instrumental evaluation. Results from various instrumental evaluation techniques (videostroboscopy, aerodynamics, electroglottography and electromyography) can be registered by the protocol, including an extensive acoustic analysis based on sustained productions of /a, i, u, ɔ/, CAPE-V sentences and reading a passage. The complete protocol provides data to test different methods applied to voice function assessment. The focus of our research was performance improvement of assessment methods used by voice clinicians.
2.2. Training programme
The user interface, terminology, audio and video samples of the GRBAS CD and DVD developed by JSLP [39] were used as a standard reference to design (according to the most recent ASHA and JSLP guidelines), the training programme described in the subsequent text.
Forty-five EP speakers from the Advanced Voice Function Assessment Databases (AVFAD) (see Jesus et al. [40] in this book for a detailed description) were used as auditory stimuli. Fifteen participants were selected for anchors, 15 for training and 15 for evaluation.
The voices from the AVFAD were selected based on the auditory perception in a quiet room by a speech and language therapist (the second author of this book chapter) using VLC media player 2.1.3. rincewind running on a laptop connected to a pair of NGS 2.1 loudspeakers. The same speech and language therapist classified the representative samples (anchors) of all selected voices with the GRBAS and CAPE scales.
Judges listened to sustained productions of vowels/a, i/played in a quiet environment with the same volume through a pair of Sennheiser HD380Pro headphones connected to the internal soundcard of a laptop computer.
Ten female speech and language therapists were asked to rate the severity of dysphonic voice stimuli using the GRBAS and CAPE-V scales. Each judge first evaluated 15 voices without any training and then went through a training programme based on two 1-h sessions.
During the first session, judges read detailed written instructions and the original description of the scale, and then, classified anchor voices that included several grades of severity for vocal quality. During the second session, a new set of voices (training voices) were classified, and judges could listen to one anchor for each five voices that were classified. At the end of the second session, all judges had access to a feedback document, but they could not change their classifications. One week later, the same judges classified a new set of 15 voices.
IBM SPSS Statistics 23 was used to calculate the Intraclass Correlation Coefficient (ICC) of responses and to run a one-way analysis of variance (ANOVA) with repeated measures.
3. Results
3.1. Cross-cultural adaptation and translation of the GRBAS and CAPE-V scales
Two EP translations of the original American English CAPE-V scoresheet and instructions were produced by two independent translators. This led to the detection of errors and divergent interpretations of ambiguous items in the original tool [33]. The translators were fluent in both languages (with the target language as their mother tongue), knowledgeable of the two cultures, and experts in the content measured by the instrument (they were both SLTs). Then, both translators synthesised the results of the translations, producing one common translation, which was used to back-translate the assessment tool, producing as many back-translations as translations (two). An expert committee compared the source and the final versions and produced a pre-final version for field testing, based on all translations and back-translations.
During CAPE-V’s cognitive debriefing (final stage of the cross-cultural adaptation and translation), alternative wording and interpretation of the translation were tested in five clients with voice pathology by the second author of this book chapter (a SLT), at the University of Algarve. Finally, the translation was revised taking into account the feedback obtained.
Hirano’s ([12], pp. 83–84) GRBAS description was translated by the same group of experts involved in CAPE-V’s cross-cultural adaption, using exactly the same process and stages [33].
A professional Japanese translator (Tomoko Suga) certified by the Japanese embassy in Lisbon (Portugal) translated the original Takahashi ([11], pp. 181–209) instructions. The translator was fluent in both languages (Japanese and EP) and knowledgeable of the two cultures. Since the original Japanese used by Takahashi ([11], pp. 181–209) is quite different, in some respects, from what is used nowadays and scientific terminology has changed considerably, only the core descriptions by Takahashi ([11], pp. 181–209) were retained in the Portuguese version, and the translation had to be thoroughly revised by an expert committee that included the original Japanese translator, the first author of this book chapter and an SLT blind to the purposes of the study.
The same group of five clients with voice pathology recruited for CAPE-V’s cognitive debriefing was involved in Takahashi’s ([11], pp. 181–209) and Hirano’s ([12], pp. 83–84) GRBAS analysis of the level of comprehensibility of the instructions and the final items, cognitive equivalence of the translation, translation alternatives and items that were eventually inappropriate or confusing.
CAPE-V’s cognitive debriefing results showed no inconsistencies but GRBAS’ instructions analysis revealed that the number of vowels required by later protocol is not the same as currently suggested by ASHA [13] or in most recent voice assessment procedure based on sustained vowels.
According to Takahashi ([11], pp. 181–209), clinicians should perceptually evaluate five sustained vowels [a, ɛ, i, ɔ, u] and choose to register, on a table that is part of the score sheet, the one that they attribute the highest GRBAS parameters scores.
The use of sustained vowels usually results in articulatory stability and allows the clinician to focus on the typology a voice source signal that is more regular and stable than in connected speech, facilitating the perceptual assessment of voice quality [41, 42].
Given the fact that the CAPE-V protocol [13] proposes [a, i] as the sustained vowels to be used during assessment, and that both GRBAS and CAPE-V are used by the University of Aveiro’s Voice Evaluation Protocol [18], following cognitive debriefing, these were proposed as the basis of perceptual evaluation. According to ASHA ([13], p. 3), [i] is used because it is the only sound speakers that can produce during laryngeal videoendoscopy, and /a/ is used because it differs from /i/ in terms of its degree of tenseness: /a/ is a lax vowel and /i/ is a tense vowel in most English dialects. Portuguese does not have the tense-lax contrast, but still, the close /i/ versus open /a/ distinction could be used to monitor the effect of an enlarged pharyngeal cavity for close vowels ([43], p. 627) and the lowering of laryngeal structures ([43], p. 633) for open vowels.
The translations were revised taking into account the results from the cognitive debriefing process, and the assessment tools can now be administered to a representative sample of the population. Both Takahashi’s ([11], pp. 181–209) and Hirano’s ([12], pp. 83–84) instructions in Portuguese are now included in the University of Aveiro’s Voice Evaluation Protocol [18] manual and available from the ACSA platform.
3.2. Training programme
The GRBAS CD and DVD [39] were thoroughly analysed (see Figure 1); terminology, audio and video samples therein were used as a standard reference to design the training programme (described earlier).
Figure 1.
Case (left) and drill (right) user interfaces from the GRBAS DVD [39].
This resulted in a first prototype of a PowerPoint presentation, shown in Figure 2, based on Japanese audio and video samples [39] that guided the final PowerPoint presentation design that then used audio samples from the Portuguese AVFAD [40].
Figure 2.
GRBAS PowerPoint prototype presentation using samples from JSLP [39].
The anchors were available during the training programme on a PowerPoint 2010 presentation with a total of 15 slides formatted as shown in Figure 3.
Figure 3.
Screenshot from the PowerPoint presentation used to run the training programme. Samples (anchors) of female voices with GRBAS and CAPE-V classifications are shown.
The ICC is a measure of inter-rater reliability that describes the similarity between the responses observed within a given set. The ICC value varies between 0 and 1, the closer to 1, the more consistent are the results.
The ICC mean of 10 raters for the parameters of the GRBAS scale is presented in Table 1.
Pre-training
Post-training
G
0.963
0.959
R
0.949
0.947
B
0.907
0.886
A
0.937
0.832
S
0.886
0.907
Table 1.
ICC for the parameters of the GRBAS scale pre- and post-training.
All ICC values (pre- and post-training) are very high which indicates a good agreement between judges. We could only observe a post-training increase of ICC values for the Strain parameter which suggests that the training programme was not very effective. However, since the pre-training values are already very high, it is harder to observe an increase of the values after training as a result of the training programme. The Strain parameter is the only one with a mean ICC value below 0.900 pre-training, so a possible cause for the difficulty in observing the expected effect of training in the other parameters could be related to the fact that the ICC values pre-training are above a certain threshold. Still, even with evaluator distinct pre-training standards (different GRBAS parameter values), all changed classifications post-training.
We also ran a one-way ANOVA with repeated measures for the GRBAS scale. This analysis allowed us to test if the evaluators changed the classifications as a function of time (pre- to post-training) and how this change relates to possible differences between them. The results are shown in Table 2.
Time
Judge
Time × Judge
G
0.000
0.008
0.000
R
0.000
0.598
0.000
B
0.001
0.069
0.000
A
0.000
0.000
0.001
S
0.000
0.002
0.006
Table 2.
p-Values of the repeated measure ANOVA for the parameters of the GRBAS scale with the judges as between subject factor and time as within subjects factor.
From Table 2, it can be seen that time is a significant effect for all parameters and the interaction also. As for the differences between raters, as a main effect, only for the Rough and the Breathy parameters, these are not significant.
The ICC mean of 10 raters for the parameters of the CAPE-V scale is presented in Table 3.
Pre-training
Post-training
Overall severity
0.975
0.970
Roughness
0.961
0.942
Breathiness
0.899
0.946
Strain
0.926
0.916
Pitch
0.895
0.788
Loudness
0.913
0.782
Table 3.
ICC for the parameters of the CAPE-V scale pre- and post-training.
Similar to what was observed for the GRBAS scale, all ICC values (pre- and post-training) are quite high which indicates a good agreement between judges. We could only observe a post-training increase of ICC values for the Breathiness parameter which suggests that the training programme was not very effective. However, when analysing the CAPE-V parameter values, all evaluators changed in the same direction from pre- to post-training, that is, all 10 evaluators either presented higher or lower values post-training for a specific parameter.
We also ran a one-way ANOVA with repeated measures for the CAPE-V scale. The results are shown in Table 4.
Time
Judge
Time × Judge
Overall severity
0.000
0.027
0.000
Roughness
0.000
0.022
0.000
Breathiness
0.000
0.000
0.000
Strain
0.000
0.000
0.000
Pitch
0.042
0.004
0.021
Loudness
0.022
0.001
0.015
Table 4.
p-Values of the repeated measure ANOVA for the parameters of the CAPE-V scale with the judges as between subject factor and time as within subjects factor.
From Table 4, it can be seen that both the effects and their interaction are significant for all the parameters.
4. Conclusions
One of the major contributions of this work was the development of the first non-Japanese version of the original manual of the GRBAS scale and the first Portuguese version of the detailed design considerations, description and instructions of CAPE-V. This research followed international guidelines for the translation and cultural adaptation of health assessment tools.
The GRBAS and CAPE-V scales are now part of the following comprehensive and unique set of resources developed for clinicians at the University of Aveiro in Portugal: A standardised voice case history form [44, 45]; a voice evaluation protocol [18]; a reference voice database [40]. All of these are freely available from the ACSA platform.
The manuals developed during this project had a crucial impact on the training of judges. The ICC values were generally very high, which could be the result of the written instructions and detailed description of the scales, which is a possible cause for the small training effect. The definition of the Breathiness parameter benefited particularly from the availability of these instructions. Problems related to the use of the Portuguese term for Grade ‘grau de rouquidão’ being erroneously interpreted as the CAPE-V term ‘rouquidão’ (Roughness), as previously reported by Jesus et al. ([16], p. 62), have been circumvented by the manual, training and samples of voices that represent specified grades of severity.
We also ran a one-way ANOVA with repeated measures for the GRBAS and CAPE-V scales. This analysis allowed us to test if the evaluators changed the classifications as a function of time (pre- to post-training) and how this change relates to possible differences between them.
Regarding the analysis of variance, taking into account the time factor as the main object of study, results showed pre- to post-training differences. The evaluators had individual and distinct standards, and changed the classifications, allowing us to conclude that their internal standards have been modified.
Increasing the level of experience of the evaluators, or the number of training sessions, could have contributed to reducing the variability of the results.
Acknowledgments
This book chapter is dedicated to Lília Brinca.
The authors would like to thank the Otorhinolaryngology teams from Hospital de Santo António, Hospital de São João and Hospital Pedro Hispano. We would also like to thank all the undergraduate and postgraduate students that contributed along the years to data collection and annotation. A special thanks to our colleague Maria Teresa Roberto.
This research was partially funded by National Funds through FCT (Foundation for Science and Technology) in the context of the projects UID/MAT/04106/2013 and UID/CEC/00127/2013.
The AVFAD project was supported by the School of Health Sciences (ESSUA), University of Aveiro, Portugal.
This work was developed as part of the M.Sc. in Speech and Hearing Sciences at the University of Aveiro, Portugal: Tavares, A. (2014). Avaliação Percetiva da Voz: GRBAS e CAPE-V [Perceptual Evaluation of Voice: GRBAS and CAPE-V]. M.Sc. Thesis, Mestrado em Ciências da Fala e da Audição [M.Sc. in Speech and Hearing Sciences], University of Aveiro, Portugal.
\n',keywords:"voice, voice disorders, perceptual voice evaluation, GRBAS, CAPE-V, American Speech-Language-Hearing Association, simulation training",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/56042.pdf",chapterXML:"https://mts.intechopen.com/source/xml/56042.xml",downloadPdfUrl:"/chapter/pdf-download/56042",previewPdfUrl:"/chapter/pdf-preview/56042",totalDownloads:1500,totalViews:351,totalCrossrefCites:1,totalDimensionsCites:3,totalAltmetricsMentions:1,impactScore:3,impactScorePercentile:81,impactScoreQuartile:4,hasAltmetrics:1,dateSubmitted:"December 1st 2016",dateReviewed:null,datePrePublished:null,datePublished:"September 13th 2017",dateFinished:"June 15th 2017",readingETA:"0",abstract:"Several methods have been proposed for the perceptual evaluation of voice quality, but the GRBAS and Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V) scales are the most widely used and recommended as part of standardised voice evaluation protocols. In this study, cross-cultural adaptation and translation of the GRBAS (the first translation from the original Japanese version) and CAPE-V scales to European Portuguese were carried out following international guidelines. Results from a study of the intra- and inter-rater reliability of the perceptual evaluation of voices with the GRBAS and CAPE-V scales, before and after a training programme, designed according to the most recent American Speech-Language-Hearing Association and Japan Society of Logopedics and Phoniatrics guidelines, are also reported.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/56042",risUrl:"/chapter/ris/56042",book:{id:"5957",slug:"advances-in-speech-language-pathology"},signatures:"Luis M.T. Jesus, Ana Inês Tavares and Andreia Hall",authors:[{id:"202906",title:"Dr.",name:"Luis",middleName:null,surname:"Jesus",fullName:"Luis Jesus",slug:"luis-jesus",email:"lmtj@ua.pt",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"204680",title:"Mrs.",name:"Ana Inês",middleName:null,surname:"Tavares",fullName:"Ana Inês Tavares",slug:"ana-ines-tavares",email:"inestavares.tf@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"204681",title:"Dr.",name:"Andreia",middleName:null,surname:"Hall",fullName:"Andreia Hall",slug:"andreia-hall",email:"andreia.hall@ua.pt",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1. Vocal evaluation",level:"2"},{id:"sec_2_2",title:"1.2. Auditory-perceptual training of evaluators",level:"2"},{id:"sec_3_2",title:"1.3. Cross-cultural adaptation and translation of the GRBAS and CAPE-V scales",level:"2"},{id:"sec_5",title:"2. Method",level:"1"},{id:"sec_5_2",title:"2.1. Cross-cultural adaptation and translation of the GRBAS and CAPE-V scales",level:"2"},{id:"sec_6_2",title:"2.2. Training programme",level:"2"},{id:"sec_8",title:"3. Results",level:"1"},{id:"sec_8_2",title:"3.1. Cross-cultural adaptation and translation of the GRBAS and CAPE-V scales",level:"2"},{id:"sec_9_2",title:"3.2. Training programme",level:"2"},{id:"sec_11",title:"4. Conclusions",level:"1"},{id:"sec_12",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Titze I, Alipour F. The Myoelastic Aerodynamic Theory of Phonation. Denver: The National Center for Voice and Speech; 2006'},{id:"B2",body:'Seikel J, King D, Drumright D. 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The effect of anchors and training on the reliability of voice quality ratings for different types of speech stimuli. Journal of Voice. 2015;29(6):776.e7-776.e14'},{id:"B33",body:'Valente A, Jesus L, Roberto M, Leahy M, St. Louis K. Cross-cultural adaptation of the Public Opinion Survey of Human Attributes (POSHA-S): The European Portuguese (EP) translation and adaptation process as a model. In: Santiago D, editor. Stuttering: Risk Factors, Public Attitudes and Impact on Psychological Well-Being. New York, NY: Nova Science; 2015. pp. 93-110'},{id:"B34",body:'Hutchinson A, Bentzen N, Zahn C, editors. Cross Cultural Health Outcome Assessment: A User’s Guide. Ruinen: European Research Group on Health Outcomes; 1997'},{id:"B35",body:'Wild D, Grove A, Martin M, Eremenco S, McElroy S, Lorenz A, Erikson P. 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Protocolo de Anamnese Vocal (Jovens e Adultos) da Universidade de Aveiro [University of Aveiro’s Standard Voice Case History Form]. University of Aveiro, Portugal. 2010. INPI Registration Number 463523 and IGAC Registration 27/05/2010. Available from: Advanced Communication and Swallowing Assessment (ACSA) http://acsa.web.ua.pt/'},{id:"B45",body:'Ferreira M, Jesus L, Couto P, Vilarinho H. University of Aveiro’s Standardised Voice Case History Form. Revista de Saúde Pública 48 (Special Number); 2014. p. 297'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Luis M.T. Jesus",address:"lmtj@ua.pt",affiliation:'
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1. Introduction
The Federal Automated Vehicles Policy [2] document released by NHTSA in September 2016 states that 35,092 people died on US roadways in 2015 and 94% of the crashes were attributed to human error. Highly automated vehicles (HAVs) have the potential to mitigate most of these crashes. They also have such advantages as not being emotional, not fatiguing like humans, learning from past mistakes of their own and other HAVs, being able to use complementary technologies like Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) – which could further enhance system performance. Add in the potential to save energy and reduce pollution (better fuel economy, ride sharing and electrification) – creating a huge impetus to implement autonomous vehicle technology as soon as possible.
On the other hand we have the consumer industry from Silicon Valley eyeing autonomous vehicles as a huge platform to engage, interact, customize and monetize the user experience. Think online shopping, watching a movie, doing your email or office work, video chats, customized advertisements based on user profile and location, etc. – all while our transport takes us to our destination. The innovation and business potential presented by the HAVs is only limited by imagination and savvy to overcome the challenges.
Among the various challenges to overcome are those of sensing the environment around and even inside the vehicle. Two of these sensing technologies are LIDAR and camera. Each of them are evolving fast to meet the industry demands. Levels 3–5 of autonomous vehicles as defined by NHTSA and SAE (Table 1) will need a high resolution and long range scanning LIDAR [3]. They will also need cameras which operate in infrared (and visible) spectrum to be able to function at night and low light conditions.
Level
Name
Narrative definition
Dynamic Driving Task (DDT)
DDT fallback
Operational Design Domain (ODD)
Sustained lateral and longitudinal vehicle motion control
Object and Event Detection and Response (OEDR)
Driver performs part or all of the Dynamic Driving Task (DDT)
0
No Driving Automation
The performance by the driver of the entire DDT, even when enhanced by active safety systems.
Driver
Driver
Driver
n/a
1
Driver Assistance
The sustained and ODD-specific execution by a driving automation system of either the lateral or the longitudinal vehicle motion control subtask of the DDT (but not both simultaneously) with the expectation that the driver performs the remainder of the DDT.
Driver and System
Driver
Driver
Limited
2
Partial Driving Automation
The sustained and ODD-specific execution by a driving automation system of both the lateral and longitudinal vehicle motion control subtasks of the DDT with the expectation that the driver completes the OEDR subtask and supervises the driving automation system.
System
Driver
Driver
Limited
Automated Driving System (“System”) performs the entire DDT (while engaged)
3
Conditional Driving Automation
The sustained and ODD-specific performance by an ADS of the entire DDT with the expectation that the DDT fallback-ready user is receptive to ADS-issued requests to intervene, as well as to DDT performance-relevant system failures in other vehicle systems, and will respond appropriately.
System
System
Fallback ready user (Driver is fallback)
Limited
4
High Driving Automation
The sustained and ODD-specific performance by an ADS of the entire DDT and DDT fallback without any expectation that a user will respond to a request to intervene.
System
System
System
Limited
5
Full Driving Automation
The sustained and unconditional (i.e., not ODD-specific) performance by an ADS of the entire DDT and DDT fallback without any expectation that a user will respond to a request to intervene.
System
System
System
Unlimited
Table 1.
SAE J3016 – summary of levels of driving automation [3].
We will start with discussing the infrared spectrum, its advantages and disadvantages and then move onto LIDAR and Camera in some level of detail.
2. Infrared spectrum
2.1. Infrared radiation
The sun radiates electromagnetic energy in a wide spectrum from the shortest X-rays to radio waves. Figure 1 shows the portion visible to the human eye (~380–750 nm) and the infrared region [4]. The near infrared region (~750–1400 nm) is used in many sensing applications including the night vision camera and LIDAR. The active night vision cameras (use light from artificial sources) are different from the passive thermal imaging cameras which operate at higher wavelengths (8–15 μm) and use natural heat as sources of radiation. Figure 1 also shows the wide range of infrared radiation from 750 nm to 1 mm wavelength.
Figure 1.
Electromagnetic spectrum with visible light highlighted [4].
2.2. Sensitivity
Figure 2 shows the human eye and camera sensitivity to the visible – Near infrared (NIR) spectrum. The advantage and disadvantage for sensing applications primarily arises from the fact that infrared is mostly invisible in the far field. A fair amount of red color can be seen by most humans till 850 nm; beyond that lies a fair amount of subjectivity. The fact that the human eye is not very sensitive to NIR light allows cameras to be used unobtrusively (especially at night/poor lighting conditions). The disadvantage lies in the fact that silicon based image sensors have poor sensitivity in this wavelength (~35% QE at 850 and 10% at 940 nm). In addition these wavelengths can reach the retina of the eye – so the exposure has to be controlled to avoid damage.
Figure 2.
Sensitivity of photo detectors and cameras vs. human eye.
2.3. Spectral irradiance
The solar radiation outside the earth’s atmosphere and that reaching the surface is shown in Figure 3 [8].
Figure 3.
Solar spectral irradiance on earth [8].
Dips in the spectral irradiance at surface are primarily due to water in the atmosphere. In the infrared spectrum of interest they occur at 810, 935, 1130, 1380, 1880 nm and beyond. This means the ambient noise is lower at these specific wavelengths. However, wavelengths of many semiconductor devices shift with temperature (~0.3 nm/°C for Gallium arsenide and aluminum gallium arsenide materials used in infrared spectrum); for automotive applications this shift is ~44 nm from −40 to 105°C. Ideally we need a peak with flat ambient noise variation around it for good design.
Another observation from Figure 3 is the lower ambient noise as we go to the longer wavelengths. However, past ~1000 nm the material base for detectors changes from silicon to germanium or indium gallium arsenide – which can be expensive.
3. Light Detection And Ranging (LIDAR)
3.1. Need for LIDAR in automotive
LIDAR, RAdio Detection And Ranging (RADAR) and Camera are the environment sensors central to the autonomous car operation. They are used to detect and classify the objects around the car by location and velocity. Each of the sensors has limitations and the information obtained from them is fused together with confidence prior to making a decision on the vehicles trajectory.
Table 2 provides a brief summary of the above sensing technologies.
The Time of Flight LIDAR operation can be explained using Figure 4.
Figure 4.
Time-of-Flight FLASH LIDAR.
A laser is used to illuminate or “FLASH” the field of view to be sensed. The laser pulse travels till it is reflected off a target and returned to a detector. The time taken for the pulse to travel back and forth provides the range. The location of the target is based off optics mapped over the field of view and detector array. Two or more pulses from the target provide the velocity. The angular resolution depends on the number of detector pixels which map the field of view. The more pixels we have – the better the resolution.
The same principle is used by 3D cameras or high resolution flash LIDAR. Higher power and more detector pixels are used.
3.4. Emitter and detector options
As shown in Figure 4, to increase the range by 2× – the needed power is 4×. As we increase the power – we start running into eye safety limits. Infrared light below 1400 nm can reach the retina of the eye. If the exposure limit is exceeded, permanent eye damage can occur.
There are many levers available to achieve the needed range – including better detectors, bigger lenses, and shorter pulse widths. Of course, the best option would be to use light above the 1400 nm wavelength. However, to use lasers and detectors in this wavelength region (>1400 nm) – we typically have to use more expensive materials (indium-gallium-arsenide—phosphide lasers and germanium-based detectors).
3.5. Eye safety
Sunlight on the earth’s surface is composed of ~52% infrared (>700 nm), ~43% visible (400–700 nm) and ~3% Ultraviolet (<400 nm) [9]. The intensity of infrared is low enough that it does not cause eye damage under normal exposure. When light is visible and bright, the eye has a natural blink response and we do not stare at it – helping to avoid eye damage. Infrared light is not visible and so can cause eye damage if exposure limits are not regulated.
The safe levels of infrared levels are regulated by IEC-62471 for Light Emitting Diodes and IEC-60825 (2014) for lasers. In USA, the equivalent federal standards are in 21 CFR 1040 (Code of Federal Regulations).
The standards have hazard exposure limits for the cornea of the eye, thermal hazard limit for skin and eye retinal thermal hazard exposure. For exposures above 1000 s, the irradiance limit is 100 W/m2 at room temperature and 400 W/m2 at 0°C. The retina exposure limits tend to be more stringent. The calculations are complex and depend on wavelength, size of the emitter, exposure time and other factors.
3.6. Signal processing challenges
As sensors demand higher resolution and faster response – it increase the computational needs. At the raw signal level, using the forward camera as an example:
Number of pixels to be processed = frames per seconds × horizontal field of view/resolution × vertical field of view/resolution.
A similar amount of data needs to be processed by the LIDAR, RADAR and other sensors. At some level, this information has to be fused to recognize and classify objects and their trajectory.
As more and more sensing data is collected, processed and acted upon in real time (time between collection and use is extremely short), creating ways of storing/processing and updating data are being developed. For example – the 3 dimensional roadway maps needed for autonomous driving are stored in the cloud (remote server) and real time data is processed to look only for changes and updates; thus reducing the amount of data crunching to be done in real time. Another trend is to collect and process the raw analog signal when possible – thus reducing the downstream processing needs.
Security of data in autonomous vehicles is another growing concern and business opportunity for innovation. Automotive Information Sharing and Analysis Center (Auto-ISAC) (www.automotiveisac.com) was formed in 2015 by automakers to share the best practices related to cyber threats in the connected car.
4. Camera
Camera’s in automobiles continue to grow as their functional versatility is exploited with increasing innovation. They have become central to Advanced Driver Assistance Systems (ADAS) like adaptive cruise control, adaptive high beam, automatic emergency braking, lane departure warning, blind spot detection, driver monitoring, traffic sign detection and others.
The latest Tesla Model 3 is believed to have up to eight exterior cameras. Other OEM’s are also using interior driver monitoring and gesture recognition cameras. A presentation from IHS Markit [13] shows typically five exterior and one interior camera for Level 3; eight exterior cameras and 1 interior camera for Level 4 being planned by a number of Original Equipment Manufacturers.
4.1. Exterior infrared camera (night vision)
Cameras need light to illuminate the objects in its field of view. Currently most cameras used in ADAS functions work with visible light – which is fine for daytime operation. However, at night the prime source for visible light is usually the headlamps of the car. The visible light from the headlamps is strictly regulated by NHTSA with its Federal Motor Vehicles Safety Standard 108 (FMVSS 108). Figure 5 below shows a bird’s eye view of the permitted illumination region in the USA.
Figure 5.
FMVSS 108 low beam visible light illumination.
It can be observed that in essence, visible light can only be legally used for a limited range of ~60 m in front of the vehicle. Illumination outside the car lane and around the car is very limited (if any). These legal requirements are not expected to be changed anytime soon – since we will have cars driven by humans for at least another 20–30 years. This means to illuminate to longer and wider fields of view, the cameras have to work with infrared light (which is not regulated by FMVSS 108). As long as the infrared light is within eye safe limits, it can be used all around the car.
Figure 6 shows a graphic overview of the regions around the car that are covered by cameras. The forward camera needs to ideally sense as far as the RADAR and LIDAR to permit good sensor fusion.
Figure 6.
Environment sensors needed for autonomous cars.
The target range for RADAR and LIDAR is at least 200 m (Forward direction) and 50–100 m in all other directions.
4.2. Exterior camera illumination challenges
The spectral sensitivity of CMOS image sensors at 850 nm is ~35% compared to its peak at 550 nm (green). Further down at 940 nm, this reduces to ~10%. This means a larger number of infrared photons is needed to generate a clear image.
To illuminate targets at longer ranges and wider field of view more light is needed. In addition, different targets have different reflectivity – which can have a significant effect on the image quality. So while we put out more and more light to get a better signal – we need to ensure the intensity is still eye safe. We also start eating up more energy from the battery for illumination. Calculations show the amount of infrared flux needed could be anywhere from 6 W (100 m range, 12° FOV, 50% reflectivity, 850 nm, 0.15 μW/cm2, Lens F#1) to 1250 W (200 m range, 40° FOV, 10% reflectivity, 850 nm, 0.15 μW/cm2, Lens F#1) [10, 11].
A typical headlamp today may have 5 W of visible light used per lamp currently. Imagine the complexity of adding 100’s of more Watts to the headlamp. The self-driving eco system has not yet come to grasp the scope of challenge that it has to deal with here. The alternative would be to rely more on the LIDAR and RADAR sensors at the longer ranges and use the camera only in the short ranges. This option may not provide needed reliability – since all of these technologies have weakness (RADAR does not same resolution as camera at long ranges and LIDAR is more prone to poor performance in bad weather).
Potential solution options which have not been fully vetted are to use pulsed infrared lasers to illuminate the CMOS based cameras; use of infrared matrix lighting architectures where rows of LED’s are turned on in sequence with a rolling shutter camera more to come as we make progress.
4.3. Interior camera – market need
The need for an interior camera arises out of multiple market forces. The first is the introduction of self-driving cars which are autonomous only in certain driving conditions (highways/traffic Jams). The cars switch between the human driver and the computer as needed. To do this effectively, the human driver has to be monitored as part of the environment in and around the car. This is to ensure adequate warning is given to the driver to leave their current engagement and get ready to take over the task of driving.
The second market force is the increase of distracted driving. In 2014, 3179 (10% of Total) people were killed and an additional 431,000 (18% of total) were injured in collisions involving distracted drivers in the USA [10]. NHTSA has a blueprint to reduce accidents related to distracted driving – which encourages OEM’s to put in place measures to ensure the driver keeps their eyes on the road when the vehicle is moving. A definition of distraction in terms of driver gaze and time elapsed away from looking straight is provided in other-related NHTSA documents [12]. At a high level, looking more than 2 s in a direction 30° sideways of up-down when the vehicle speed is more than 5 mph would be classified as distracted. The increase in distracted driving is attributed to cell phone/smartphone/texting and related activities.
Additional benefits and applications are continuing to generate from the driver monitoring infrared camera system. It lends itself well to also catch drowsy drivers (eyelids shut or drowsy pupils); face recognition – not strong enough to be a biometric device, but enough to at least enable customized settings for different drivers in family and many more to come.
The auto industry is responding to these two needs (autonomous cars, distracted driving) by installing an infrared camera to monitor the gaze of the driver. Infrared illumination is needed – since we do not want to distract the driver at night with visible light. The wavelength for illumination is in the 850–950 nm range. The eye safety and camera sensitivity challenges of illumination in this spectrum were briefly discussed earlier sections. A few other challenges are discussed in the next section.
4.4. Interior camera illumination challenges
When we use an infrared camera facing the driver, the LED’s are shining the light right on our eyes and face. Light at 850 nm can be red enough to be seen easily by most people – especially at night. Measures to put in a dark filter and smudge the bright red LED spot with optics are partially successful. The problem arises from the fact that anything done to reduce the brightness will usually also reduce the illumination – which would result in poor image quality and failure to detect distraction in gaze by the software processing the image.
One solution is to go to higher wavelengths (940 nm) – the challenge here is lower camera sensitivity. This has been overcome by pulsing higher peak currents at lower duty cycle using a global shutter image sensor. The typical cameras used are 30 fps and these are fast enough – since gaze while driving does not change that often and fast.
On the eye safety side, measures are needed to ensure that when the eyes are too close to the Infrared LED (IRED) – then they either need to be shutoff or reduced in intensity. Typically the distance to the eye is estimated with the camera itself, as an added measure we can have proximity sensors.
Since these cameras work in infrared with a filter block for visible wavelengths, the biggest challenge for illumination tends to be during daytime under full sunlight. The IREDs have to typically overcome ambient noise from the sun. Polaroid sunglasses can also sometimes prevent function if the coating prevents the wavelength to pass through.
The last challenge worth mentioning is that of consumer acceptance and loss of privacy. From a legal perspective, if the camera is recording the driver’s face – the information can be pulled up in court if needed by a lawyer. NHTSA regulations mandate that any information needed for vehicle safety has to be stored for a short direction – essentially a black box (As used in aircrafts) to help reconstruct an accident. Will consumers trade a loss of privacy for safety and convenience (of automated driving) is yet to be seen. OEM’s may initially provide consumers with the option to turn off the camera (and related loss of function) to enable the transition.
4.5. Additional applications for interior camera
OEMs are evaluating the concept of using interior cameras to monitor all occupants in the car – to enable optimum deployment of airbags and other passive safety devices. At a basic level, if there is no occupant in the passenger seat (or just a cargo box) – do not deploy the airbag.
Another application is the use of gesture recognition. The idea is use gesture’s seamlessly and conveniently to open windows/sunroofs/turn on radio/change albums/etc. The successful combination of voice, touch and gesture to operate devices depend a lot on the age group (and resultant car design) and how well the technologies are implemented.
Face recognition and iris recognition are already making their way into smartphones. They are expected to penetrate the auto market. Even through the technologies are available and mature, the business case/consumer demand/willingness to pay for these functions is yet to be explored.
4.6. Signal processing
As cameras become ubiquitous around the car, the questions become how many cameras are enough and what should be the range and resolution of the cameras. The same question can be asked of LIDAR and RADAR also. However, signal processing tends to be more demanding the high resolution (comparatively) of cameras.
Assuming a VGA format for the image sensor, we get 480 (H) × 640 (W) pixels per frame; with typically 30 fps coming in for processing. The resolution we get from this VGA image sensor depends on the optical field of view it covers and the maximum range at which the smallest object has to be recognized and resolved for action. At 100 m and a 40° HFOV the width covered by the 640 pixels is ~7279 cm. This means each pixel covers 11.4 cm or ~4.5 in. Is this level of resolution good enough for self-driving cars? The next section digs a little deeper into this topic.
4.7. Exterior camera resolution requirement
What is the smallest object that can change the trajectory of the car? One could argue this could be as small as a nail or sharp object on the road. Maybe with the newer tires which can roll over nails, we can overlook this object (They would then become mandatory for self-driving cars). The next object I can think of would be a solid brick placed on the road which even though small, could change the trajectory of the car. Other such objects like tires, tin cans, potholes, etc. could be imagined that would have a similar impact.
The autonomous car machine vision has to detect such an object at a far enough distance to take appropriate measures (steer, brake/slow down or prepare for collision). With a speed of 100 mph and a dry road with friction of 0.7, a braking/sensing range of 190 m is calculated [13]. A modular USA brick with dimensions of 194 × 92 × 57 mm would subtend an angle of ~2 arc min (tan−1 65/100,000). This level of resolution would be outside the capability of a standard VGA camera.
After detection, the object has to be classified before an action can be taken on how to deal with it. The kinds of objects the car could come across on its path depends very much geo fenced location. Objects on the US road freeways and urban streets could be very different from those in India or china. This is the point where the admiration for the human senses and brain capacity start daunting current computer chips.
5. Sensor fusion
5.1. Need for sensor fusion
For self-driving cars to be accepted by society, they would have to demonstrate significantly lower probability of collision – when compared to human drivers. A 2016 study by Virginia Tech Transportation Institute [14] found that self-driving cars would be a comparable or a little better than humans for severe crashes, but significantly better at avoiding low severity level crashes (level 3). The level 3 crash rate was calculated at 14.4 crashes per million miles driven for humans and 5.6 crashes for self-driving cars.
To keep things in perspective, we could estimate an average person in USA to drive 900,000 miles in their lifetime (12,000 miles/year × 75 years). Also note that the above report uses only Google self-driving car data. These cars are known to have a full suite of sensors (Multiple LIDAR, RADAR, Cameras, Ultrasonic, GPS and other sensors).
The point is that just like the human driver, the car has to integrate the information from multiple sensors and make the best decision possible in the circumstance. On top of that, it has to be way better to get people to start adopting the technology. Knowing that each of the sensor technologies has some limitation, the need to fuse multiple inputs reliably is a daunting task. Incorrect or poor implementation of the sensor fusion could quickly take the car back to the dealer show room.
5.2. Challenges to sensor fusion
Figure 7 below illustrates the challenge of sensor fusion.
Figure 7.
The challenge of sensor fusion – illustrated.
The objective sensor fusion is to determine the environment around the vehicle trajectory with enough resolution, confidence and latency to navigate the vehicle safely.
Figure 7 row 1 shows the ideal case when two sensors agree on an object and the object is detected early enough to navigate the car.
Figure 7 row 2 shows a case where each of the sensors classifies the object differently. In this case, the best option maybe to just agree that it is big enough object to avoid if possible.
Figure 7 row 3 similar situation where a person on a bicycle maybe identified as a person or a bicycle. Again, we could agree that it is an unidentified large moving object that needs to be avoided.
The last two rows shows smaller objects that pose difficult questions. Is it better to run over a small dog than to risk braking and getting rear-ended? Can the pothole be detected and classified early enough to navigate? Is the pothole or object small enough to run over?
These questions will take a longer time to resolve with improving technology in sensing, computing, public acceptance and legislation. The 80/20 Pareto principle would imply that the last 20% of the problems for self-driving cars will take 80% of the time it takes to bring it to mass market.
6. Conclusions
The exponential growth of electronics in the auto industry can be estimated by the number of sensors and electronic control units (ECUs) being added to each newer cars. From a 2003 VW golf (~35 ECUs, 30 sensors); a 2013 Ford Fusion (~70 ECUs, 75 Sensors) to a projection for automated car in 2030 (~120 ECUs, >100 Sensors) [1]. One could be forgiven for imagining the future car to be a supercomputer with wheels.
We are in the initial growth spurt for autonomous cars. A lot of technology still remains to be innovated and matured before regulation and standards kick-in. LIDAR technology is still evolving – range, resolution, eye safety, form factor and cost of the technology is improving rapidly. Camera hardware for medium range and VGA resolution has matured – but needs improvement in range (200 m target), resolution (>8 Megapixel) and performance under poor lighting or with infrared. Sensor fusion architectures can only be optimized after sensors needed are standardized or at least well understood. Real time operation with use of Artificial Intelligence – Neural networks is still in early stage. Society has still to debate and accept the safety performance with known behavior of these robots on wheels. What a great time for electronics and the Auto industry!
\n',keywords:"autonomous vehicles, infrared, sensors, LIDAR, camera",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/56860.pdf",chapterXML:"https://mts.intechopen.com/source/xml/56860.xml",downloadPdfUrl:"/chapter/pdf-download/56860",previewPdfUrl:"/chapter/pdf-preview/56860",totalDownloads:1780,totalViews:2229,totalCrossrefCites:7,dateSubmitted:"June 21st 2017",dateReviewed:"August 11th 2017",datePrePublished:"December 20th 2017",datePublished:"August 29th 2018",dateFinished:"September 8th 2017",readingETA:"0",abstract:"The spurt in interest and development of Autonomous vehicles is a continuing boost to the growth of electronic devices in the automotive industry. The sensing, processing, activation, feedback and control functions done by the human brain have to be replaced with electronics. The task is proving to be exhilarating and daunting at the same time. The environment sensors – RADAR (RAdio Detection And Ranging), Camera and LIDAR (Light Detection And Ranging) are enjoying a lot attention with the need for increasingly greater range and resolution being demanded by the “eyes” and faster computation by the “brain”. Even though all three and more sensors (Ultrasonic / Stereo Camera / GPS / etc.) will be used together; this chapter will focus on challenges facing Camera and LIDAR. Anywhere from 2 – 8 cameras and 1 – 2 LIDAR are expected to be part of the sensor suite needed by Autonomous vehicles – which have to function equally well in day and night. Near infrared (800 – 1000nm) devices are currently emitters of choice in these sensors. Higher range, resolution and Field of view pose many challenges to overcome with new electronic device innovations before we realize the safety and other benefits of autonomous vehicles.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/56860",risUrl:"/chapter/ris/56860",signatures:"Rajeev Thakur",book:{id:"6721",type:"book",title:"Recent Development in Optoelectronic Devices",subtitle:null,fullTitle:"Recent Development in Optoelectronic Devices",slug:"recent-development-in-optoelectronic-devices",publishedDate:"August 29th 2018",bookSignature:"Ruby Srivastava",coverURL:"https://cdn.intechopen.com/books/images_new/6721.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78923-603-3",printIsbn:"978-1-78923-602-6",pdfIsbn:"978-1-83881-672-8",isAvailableForWebshopOrdering:!0,editors:[{id:"185788",title:"Dr.",name:"Ruby",middleName:null,surname:"Srivastava",slug:"ruby-srivastava",fullName:"Ruby Srivastava"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"215089",title:"M.Sc.",name:"Rajeev",middleName:null,surname:"Thakur",fullName:"Rajeev Thakur",slug:"rajeev-thakur",email:"rajeev.thakur@osram-os.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Osram Opto Semiconductors",institutionURL:null,country:{name:"Germany"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Infrared spectrum",level:"1"},{id:"sec_2_2",title:"2.1. Infrared radiation",level:"2"},{id:"sec_3_2",title:"2.2. Sensitivity",level:"2"},{id:"sec_4_2",title:"2.3. Spectral irradiance",level:"2"},{id:"sec_6",title:"3. Light Detection And Ranging (LIDAR)",level:"1"},{id:"sec_6_2",title:"3.1. Need for LIDAR in automotive",level:"2"},{id:"sec_7_2",title:"3.2. Types",level:"2"},{id:"sec_8_2",title:"3.3. Time of Flight LIDAR Operating Principle",level:"2"},{id:"sec_9_2",title:"3.4. Emitter and detector options",level:"2"},{id:"sec_10_2",title:"3.5. Eye safety",level:"2"},{id:"sec_11_2",title:"3.6. Signal processing challenges",level:"2"},{id:"sec_13",title:"4. Camera",level:"1"},{id:"sec_13_2",title:"4.1. Exterior infrared camera (night vision)",level:"2"},{id:"sec_14_2",title:"4.2. Exterior camera illumination challenges",level:"2"},{id:"sec_15_2",title:"4.3. Interior camera – market need",level:"2"},{id:"sec_16_2",title:"4.4. Interior camera illumination challenges",level:"2"},{id:"sec_17_2",title:"4.5. Additional applications for interior camera",level:"2"},{id:"sec_18_2",title:"4.6. Signal processing",level:"2"},{id:"sec_19_2",title:"4.7. Exterior camera resolution requirement",level:"2"},{id:"sec_21",title:"5. Sensor fusion",level:"1"},{id:"sec_21_2",title:"5.1. Need for sensor fusion",level:"2"},{id:"sec_22_2",title:"5.2. Challenges to sensor fusion",level:"2"},{id:"sec_24",title:"6. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'Carlson J. Evolution of ADAS architectures, sensor fusion, and the future of the autonomous car. In: ADAS Sensors Conference (2017); 17-18 May 2017; Detroit, Michigan'},{id:"B2",body:'Federal Automated Vehicles Policy; Sept 2016; U.S Department of Transportation; www.nhtsa.gov; Docket No. NHTSA-2016-0090; page 5'},{id:"B3",body:'Surface vehicle recommended practice; Taxonomy and Definitions of terms related to driving automation systems for on-road motor vehicles; SAE J3016_201609; Table 1, page 17'},{id:"B4",body:'Philip Ronan, Gringer. Revised diagram with re-aligned spectrum; File – EM spectrum.svg and Linear visible spectrum.svg; 19 February 2013;13:51:42. Available from: https://en.wikipedia.org/wiki/Electromagnetic_radiation [Accessed: 2017-07-17]'},{id:"B5",body:'Rfcafe. Solar Spectral Irradiance & PV Cell Operational Regions (ASTM G173-03) [Internet]. 2017. Available from: http://www.rfcafe.com/references/electrical/ASTM-G173-03-Reference-Spectra.htm [Accessed: 2017-07-18]'},{id:"B6",body:'Vehicle-to-Vehicle Communications: readiness of V2V technology for application – DOT HS 812014; Table V-7; page 105'},{id:"B7",body:'Millimetre Wave Receiver concepts for 77 GHz automotive radar in silicon Germanium Technology – D.Kissenger (Springer Brief’s 2012); Table 2.1 and 2.2; Page 18'},{id:"B8",body:'Wikipedia. Sunlight [Internet]. 2001; By Nick84 - http://commons.wikimedia.org/wiki/File:Solar_spectrum_ita.svg, CC BY-SA 3.0, [Accessed: 2017-09-05]'},{id:"B9",body:'Thakur R. ADAS to autonomous – Evolution of LIDAR and infrared camera. In: ADAS Sensors Conference (2017); 17-18 May 2017; Detroit, Michigan'},{id:"B10",body:'Weber R. Infrared LED Illumination for Sensor Applications [OSRAM Opto Semiconductors Inc - Webinar]; 3 Dec 2015; Detroit, Michigan'},{id:"B11",body:'National Center for Statistics and Analysis. Distracted Driving 2014 (Traffic Safety Facts Research Note. Report No. DOT HS 812 260). Washington, DC: National Highway Traffic Safety Administration; 2016, April'},{id:"B12",body:'Department of Transportation, National Highway Traffic Safety Administration Docket No. NHTSA-2010-0053. Visual-Manual NHTSA Driver Distraction Guidelines for In-Vehicle Electronic Devices'},{id:"B13",body:'Thakur R. Infrared sensors for ADAS and beyond – LIDAR/infrared camera. In: TU-Automotive Conference (2015); 4 October 2015; Novi, Michigan'},{id:"B14",body:'Blanco M, et al; Automated Vehicle Crash Rate Comparison Using Naturalistic Data (2016); Jan 2016; Virginia Tech Transportation Institute; figure 1; page iv'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Rajeev Thakur",address:"rajeev.thakur@osram-os.com",affiliation:'
OSRAM Opto Semiconductors, Inc., Novi, United States of America
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The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null,scope:"
\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n
\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
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\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
\r\n
\r\n\t
\r\n
\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
\r\n
\r\n\t
\r\n
\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
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Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:null},{id:"318905",title:"Prof.",name:"Elvis",middleName:"Kwason",surname:"Tiburu",slug:"elvis-tiburu",fullName:"Elvis Tiburu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Ghana",country:{name:"Ghana"}}},{id:"336193",title:"Dr.",name:"Abdullah",middleName:null,surname:"Alamoudi",slug:"abdullah-alamoudi",fullName:"Abdullah Alamoudi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"318657",title:"MSc.",name:"Isabell",middleName:null,surname:"Steuding",slug:"isabell-steuding",fullName:"Isabell Steuding",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"318656",title:"BSc.",name:"Peter",middleName:null,surname:"Kußmann",slug:"peter-kussmann",fullName:"Peter Kußmann",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"338222",title:"Mrs.",name:"María José",middleName:null,surname:"Lucía Mudas",slug:"maria-jose-lucia-mudas",fullName:"María José Lucía Mudas",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}},{id:"147824",title:"Mr.",name:"Pablo",middleName:null,surname:"Revuelta Sanz",slug:"pablo-revuelta-sanz",fullName:"Pablo Revuelta Sanz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}}]}},subseries:{item:{id:"18",type:"subseries",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. 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