\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"2021",leadTitle:null,fullTitle:"Cutting Edge Research in New Technologies",title:"Cutting Edge Research in New Technologies",subtitle:null,reviewType:"peer-reviewed",abstract:'The book "Cutting Edge Research in New Technologies" presents the contributions of some researchers in modern fields of technology, serving as a valuable tool for scientists, researchers, graduate students and professionals. 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He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. 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",isbn:"978-1-80356-651-1",printIsbn:"978-1-80356-650-4",pdfIsbn:"978-1-80356-652-8",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"769f942393275479acca64e4f4fea958",bookSignature:"Dr. Bankole Kolawole Fasanya and Dr. Sridhar Krishnamurti",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11518.jpg",keywords:"Frequency, Sound Power, Absorption, Noise, Soundproof, Reflection, Inverse Square, Perception, Signal, Background Noise, Building, Noise Barrier",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 18th 2022",dateEndSecondStepPublish:"May 26th 2022",dateEndThirdStepPublish:"July 25th 2022",dateEndFourthStepPublish:"October 13th 2022",dateEndFifthStepPublish:"December 12th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"3 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Fasanya is an Assistant Professor at Purdue University, USA. Prior to his current position, he has worked in different capacities with different institutions: Senior research associate (Auditory Protection and Prevention - US Army Aeromedical Research Laboratory, Adjunct Assistant Professor-NCAT, Facilities Engineer MVA, etc). Dr. Fasanya holds a Ph.D. in Industrial and systems engineering with a specialization in ergonomics and human factors.",coeditorOneBiosketch:"Dr. Sridhar Krishnamurti is a Professor and Program Director of Audiology at Auburn University. Sridhar has\r\nauthored a book, journal articles, and book chapters in Audiology and Hearing Conservation. 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Fasanya received a BSc in Mechanical Engineering in 1999 from The Polytechnic Ibadan, Nigeria, his Master’s degree in Industrial and Systems Engineering from Morgan State University, Maryland, USA and his doctorate degree in Industrial and Systems Engineering specialized in ergonomics and human factors from North Carolina Agricultural and Technical State University, USA. His research focuses on human and environmental safety, ergonomics and human factors, auditory prevention and protection and noise assessment and control at workplaces. Dr. Fasanya is currently an assistant professor at Purdue University Northwest in Indiana, USA. He currently serves as one of the executive members of the American Hearing Conservative Association (NHCA). 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It is a highly important structure that helps in food chewing to mechanically break down the food by cutting and crushing them in preparation for swallowing and digesting. It also aids in speech and its articulation of words. Human teeth consist of 20 primary (deciduous, “baby” or “milk”) teeth in children and 32 permanent teeth in adults. Teeth are classified as incisors, canines, premolars, and molars. Incisors are primarily used for cutting the food into pieces, canines are used for tearing the tissues of the food, and molars help to grind the food into smaller substances [1].
Teeth are also important for cosmetic purposes as well. Many dental treatments are not purposefully dealt with filling and taking out a tooth, but indeed nowadays people turn out to esthetic dentistry to improve, straighten, lighten, reshape, and repair teeth as well. The field of esthetic dentistry includes the establishment of veneers, crown bridges, implants, tooth-colored filling, and teeth whitening procedures.
Tooth exfoliation starts from childhood. A young boy or girl loses the baby teeth, and it gets exfoliated in response to permanent teeth that start developing beneath them. This loss of primary teeth begins around the age of six and continues till 12 years of age. The primary teeth that are vulnerable are the upper and lower lateral incisors that shed at 7–8 years and upper canines are that shed around 10–12 years of age. Only the upper and lower first molars shed at 9–11 years of age and upper and lower second molars shed at 10–12 years of age [2].
Tooth loss is a condition that advances with the increase of age. This occurs as a result of mechanical disturbances and abnormal forces that act during the chewing process of hard substances, traumatic injury, etc. Also, a few conditions such as untreated dental caries (tooth decay) and severe periodontal (gum) disease might lead to loss of permanent teeth. Tooth decay is the primary cause of tooth loss. It is caused by the increased plaque retention on the teeth followed by bacterial invasion of the plaque. This ultimately results in dental caries and the formation of cavities. Untreated tooth cavities for a chronic period of time lead to the breakdown of the tooth. This bacterial invasion and retention of plaque deposits also affects the gums and bones attached to the tooth and loses its ability to hold the tooth. Periodontal structures are tissues that support teeth and their attachment to the bone. Diseases of the gums and bones are caused by bacterial invasion of teeth and retention of plaque. It results in diseases of the gums leading to periodontitis and detachment of supporting structures of the teeth and eventually causes tooth loss. So, the ultimate care of oral hygiene is the only preventive measure to prevent tooth loss. Good oral hygiene is the process of maintaining proper brushing of teeth two times a day with fluoridated toothpaste and frequent flossing. Regular dental check-ups every 6 months can be availed to ensure good teeth and prevent tooth loss [3].
There are a few conditions like bruxism otherwise called teeth grinding that occurs during sleep. This condition is very common in people who tend to be awake by profession at night. This tooth grinding increases the wear and tear action on the tooth and causes mechanical injury. The risk of tooth fractures is common in sportspeople, especially in football and goalie. Research reports claim that smoking is another important cause of tooth loss. Reports from countries, such as the United States, Germany, and Japan, show a strong relationship between cigarette smoking and tooth loss. The habit of smoking weakens the body’s immune response to infection and causes immunosuppression. This makes it harder to guard against a gum infection and takes a longer time to heal. Reports reveal that systemic diseases also relate to tooth loss. Conditions, such as cardiovascular diseases, diabetes mellitus, cancer, and osteoporosis, also lead to permanent tooth loss due to their secondary complications. Therefore, tooth loss is not restricted to poor oral hygiene but poor maintenance of overall health [4, 5, 6].
Missing a permanent tooth is a miserable condition. Years after years the treatment options for missing teeth are dental implants, fixed dental bridges, removable partial dentures. Dental implants are considered as the prime option by dentists to replace a single tooth. This procedure involves the surgical mounting of a titanium metal post or frame on the upper or lower jaw along with mounting the replaced missing tooth. This dental implant acts as a permanent base for the replaced tooth. This procedure is highly advantageous because the replaced dental implant resembles a natural tooth and can last for decades. It also acts independently and does not disturb the adjacent normal tooth. The next treatment option is a fixed dental bridge. This procedure provides bridging between the gaps caused by the lost tooth and involves the employment of a dental prosthesis or an artificial tooth. This dental prosthesis would be attached to adjacent teeth and bonded in place with dental cement. A removable partial denture consists of replacement teeth that are attached to a natural-looking pink base. The natural teeth also act to stabilize and hold the removable plastic base in its position place. This pink base is designed in a way that matches the color of the gums and the color of the normal teeth [7].
A dental implant is a material placed in or on the oral tissues that help to support the oral prosthesis. An ideal implant material should possess the following characteristics. It should be biocompatible and possess adequate strength, rigidity, good corrosive, and be capable of wear and fracture resistance. The principles of designing a dental implant should be much compatible with the physical properties of the material. Materials that are used for fabricating a dental implant can be considered according to the chemical composition of the implant and their biological responses. Many reports claim that these dental implants may be made from metals, ceramics, or polymers [8].
According to the American Society for testing and materials, there are six distinct types of titanium that are widely available as implant biomaterials. They are grade I, II, III, IV Cp Ti, various combinations of titanium, aluminum like alpha-beta alloy containing 6% Al and 4% V, alpha-beta titanium alloy containing 6% aluminum and 7% niobium, alpha-beta titanium alloy with non-ferrous metal. The physical and mechanical properties, such as tensile strength and osseointegration, elastic modulus, non-toxic nature, are quite different for the different alloys. The most important property related to the oxygen residuals in the metals and the other two titanium is considered as very low interstitial alloys. Among all the available alloys, the commercially prepared pure titanium alloys are generally considered as pure and mentioned in Grade I, Grade II, Grade III, and Grade IV titanium and has wide applications in implant manufacturing. Some trace elements, such as carbon, oxygen, nitrogen, and iron, are also considered in this process. Although titanium possesses many strengthening characteristics, literature reports reveal that it evokes a stronger reaction in the host causing hypersensitivity reactions, failed implants with increased concentration of titanium in peri-implanted tissues, regional nodes, and pulmonary tissues based on animal models, allergy to titanium in the form of urticaria, pruritus of the mucosa or skin, atopic dermatitis, poor fracture healing, necrosis and immunosuppression and weakening of orthopedically implanted titanium [9].
Ceramics has been widely used as a dental implant coating and it was the first introduced material in the field of implant dentistry. Hydroxyapatite is one of the most known biocompatible materials commonly used as a coating for metal implants. These hydroxyapatite coatings create a good interfacial strength between bone and implant. It provides greater implant stability and improves bone healing that lies adjacent to implants. The use of hydroxyapatite improves the capacity of osseointegration and increases the rate of rehabilitation of patients. This method of implanting decreases the time from implant insertion to final reconstruction of the implant [10]. There are various methods to coat hydroxyapatite on implants, they include sol–gel coating, electrophoretic deposition, plasma spraying, sputter-deposition, and biomimetic precipitation. Ceramic materials that are used for dental implanting and coatings. The materials used are hydroxylapatite (HA), tricalcium phosphate, fluorapatite (FA), tetracalcium phosphate, calcium pyrophosphate, brushite, bioglasses, aluminum oxide, zirconium oxide, etc. (Figure 1).
SEM-image of hydroxyapatite.
In the field of dental implanting, metals are widely selected based on factors that involve properties belong to its biomechanical characteristics, machining characteristics, and surface finishing characteristics as well. In the present day, metals, such as Co-Cr, stainless steel, and gold are quite outdated in the dental implant industry and the currently available dental metals are alloys of titanium and zirconium as well. Certain components of dental implants such as the abutment screws and some attachments of the implants are also made of alloys of gold, stainless steel, and Co-Cr. Titanium is mostly considered as an effective material by most of the dentists for its wide intraosseous applications. It has enormous and typical properties, such as lesser readily affected or corroded by the environment, high resistance to chemical dosing, and capability to repair on its own. The resistance to being deformed elastically—modulus of elasticity was very compatible with that of bone and titanium oxide [11, 12]. Although titanium is a typical material suitable for dental implanting, it faces a lot of shortfalls. These drawbacks and detrimental properties of titanium ultimately resulted in prompting the scientists to look and research the new implant from other biomaterials [13].
The next innovation to overcome the said shortfalls led to the development of ceramic implants [14]. And as a result of this zirconia is used as another material for dental inserts. This in turn contrasted with metallic components zirconia demonstrated the least particle discharge and they are thought to be dormant in the body [15]. Zirconia acts as a tooth-like shading and possesses great mechanical properties and has great biocompatibility. In such a way, it is by all accounts an appropriate dental material [16]. The utilization of zirconia implants keeps a strategic distance from the inconvenience and acquiesces to the demand of numerous patients without metal inserts. The material additionally gives high quality, crack sturdiness, and biocompatibility [17]. There are various materials used for fabricating endosseous dental implants like titanium, titanium alloy, stainless steel, alumina, carbon, bioglass, polyurethane, etc. [18, 19, 20].
A novel implant, the ceria-stabilized zirconia-alumina-aluminate composite was developed and was established for its significant effect that it is not prone to aging. This implant represents a probable alternative to the yttrium-stabilized zirconia that is used for ceramic oral implants. This implant was evaluated for its long-term stability due to its make with Ce-TZP-comp and it proved a significant lowest fracture load after combined loading/aging [21].
A variety of polymers have been utilized as dental implant materials [22]. A portion of the polymer materials is polymethylmethacrylate, polytetrafluoroethylene, polyethylene, polyurethane, and polysulfone, etc. When polymer acts as a coating layer, inferior mechanical properties, lack of adhesion to living tissues, and adverse immunologic reactions are eliminated [23, 24, 25, 26]. In the present day, polymeric materials are constrained to assemble the shock retaining segments joined into the superstructures bolstered by inserts [26]. A wide variety of biomaterials have found profound applications in the form of inserts. This type of insert in implantology requires a suitable biomaterial of choice. The presently available biomaterials, such as bioceramics and other composite biomaterials, are under higher consideration and the precise examination of such biomaterial definitely have a promising future in the field of dental applications.
Herbal medicine is an indigenous system of traditional Hindu medicine and is native to the Indian subcontinent. Contemporary practices derived from ayurvedic traditions are also a type of alternative medicine. Ayurveda recommends some daily use therapeutic procedures for the prevention of and maintenance of oral health. It involves Dant Dhavani (brushing), Jivha Lekhana (tongue scrapping), and Gandoosha (gargling) or even oil pulling and tissue regeneration therapies. Various herbs are widely used in dentistry and they are aloe vera [27], cloves [28], eucalyptus [29], peppermint [30], and turmeric [31].
Icariin, one of the traditional Chinese herbal medicines, possesses significant evidence that it strengthens bones, enhances healing of bone, inhibits osteopenic effect, and inhibits inflammation. This idea made scientists incorporate icariin for better osseointegration of dental implants and shorten the rehabilitation time of patients and the results revealed that. Evaluation of the hypothesis: Limited success has been achieved to help implant surgery in icariin significantly improved the success rate of the dental implant [32].
Another randomized trial of preparing a biocomposite osteogenic nanofiber was developed with the incorporation of polycaprolactone, hydroxyapatite, dexamethasone, gelatin, beta-glycerophosphate, and ascorbic acid along with titanium implants was developed so that it mimics the bone extracellular matrix and eventually induced osteogenesis in the peri-implant niche and also regenerates the osseous tissue. This implant was worked on rabbit models and the results revealed that a coating of osteogenic nanofibrous tissues significantly increased the magnitude of osteogenesis around the zone of peri-implant tissue and also favored the dynamics of osseointegration [33].
Cassia occidentalis Linn belongs to the family Caesalpiniaceae and is commonly called Kasondi in Hindi. It is mostly grown in the southern parts of India and the plant products have been used for various ailments and have a rich medicinal value [34]. C. occidentalis (CO) contains significant bioactive compounds, such as terpenoids, anthraquinones, and carotenoids. The plant products were reported to stimulate mineralization of the bone and osteoblastic differentiation through the activation of the PI3K-Akt/MAPKs pathway in MC3T3-E1 cells of mice [35].
Another novel dental implant synthesized a nanohydroxyapatite using different methods by utilizing the biomolecules from waste products, such as an egg-shell. In this study, an institutional controlled synthesis of nano-sized HAP was performed, which can be employed in the future for another material synthesis thereby an improved bone bonding was obtained by this novel material [36]. A novel implant synthesized with nano HAP rods was performed by an
A prepared porous scaffold using nano HAP and nylon 6,6 using a salt-leaching technique was a newly handled technique. Here HAP was dispersed on the pore walls of the scaffold bonds well with nylon 6,6 and it increased the stiffness of the scaffold. This porous scaffold acts to be effective as a three-dimensional substrate for bone tissue engineering [38]. Another method developed on dental implanting includes the synthesis of biphospho-calcium phosphate (BCP) for calcium-deficient apatites, such as enamel, dentin, and bone mineral by a process of sintering. The prepared BCP had controlled bioactivity when the HAP/βTCP ratio was controlled. This form of BCP can be used as carriers for growth factors, drug delivery systems, and in tissue engineering [39].
Another preparation included natural porous bioceramics from processing the cancellous bone. Calcined bovine bone was treated with sodium pyrophosphate and sintered to obtain HAP and was in turn converted to βTCP and BCP. This process was done to improve and increase the bioactivity of the ceramics when placed
A newly evolved technique was prepared by using BCP with different HAP/βTCP ratios and was analyzed for its bioactivity with SBF solution and osteoconductivity in rabbits. The study found that BCP with a HAP/TCP ratio of 60:40 was found to be best in showing the bioactivity and osteoconductivity compared to pure HAP and other BCP ratios. A newly developed implant was created using a coating material for orthopedic metal implants. In this study, a new bioglass was prepared and coated on Ti-based and Co-Cr alloys. This was done to enhance the cell adhesion when placed
Another novel implant was prepared by using composite material consisting of poly-L-lactide (PLLA) and bioactive glass by solvent evaporation technique. The composite was bathed and soaked in SBF for 3 days for allowing the HAP deposition on the composite. The dried composite was subjected to various characterization techniques. The study found that the bioactivity of the composite was highly increased and it, in turn, supported the composite to promote bone integration when placed
Another group of researchers synthesized a composite containing chitosan, HAP, and bioglass. Chitosan-HAP composite was prepared using calcium nitrate and orthophosphoric acid in SBF. The novel prepared composite bioactive glass was added to this preparation.
Cassia occidentalis.
Another implant was prepared with a bioglass composite film consisting of poly (3-hydroxybutyrate) and vitamin E. The incorporation of vitamin E was done to increase the protein adsorption and hydrophilicity on the surface of the film. This composite film was subjected to various characterized studies and the results reported that they can be applied [45] in tissue engineering as a better matrix material for cell adhesion [46]. Chin et al. worked on preparing a novel multi-component skin substitute by using collagen as a matrix material which typically depicts the normal architecture of the skin. This implanting material has a main advantage in producing a cost-effective bone substitute. A novel prepared magnetic fibrin incorporated with nanoparticles and characterized those nanoparticles by various physicochemical techniques using Saos 2 cells, the cell viability, adhesion, and alkaline phosphatase assay. The study revealed that the [47] material exhibited good osteogenic property and hence it can be used in bone tissue engineering .
Auxenfans et al. [48], a researcher investigated a scaffold that contains collagen and glycosaminoglycans (GAG). The matrix was seeded with fibroblast and the study found that it forms a typical reconstructed skin or hemicornea once epithelialization completes. Another study analyzed the rate of degradation of pure collagen and collagen–HAP beads using collagenase enzyme. This enzyme was able to digest pure collagen quickly compared to collagen-HAP gel beads. The HAP provides resistance for quick degradation and the matrix structure could be maintained for a greater period and it supports the cell to adhere, proliferate, and then differentiate [49].
Another research study reported the collagen type II scaffolds by cross-linking with glutaraldehyde and scaffold without cross-linking with glutaraldehyde. The study explained that the scaffolds were seeded with chondrocytes and observed the interaction of cells with the scaffold. The cell adherence on the surface of the scaffold was high which was confirmed by SEM analysis [50]. Another implant using used barium sulfate and zirconia as additives to implant as a bone cement was created to enhance the visualization through X-ray imaging. The incorporation of these additives in bone cement helps to locate the material placed in the bone defect areas [51]. Brown et al. [52, 53] formulated a bone cement consisting of tetra calcium phosphate (TTCP) and dicalcium phosphate (DCPA or DCPD) with a P/L ratio of 4:1 and mixed with water. The mixture was allowed to set for 30 min which formed calcium-deficient HAP. The formed material was hardened and molded and has wide applications in craniofacial surgery. Yamaguchi et al. [54] suggested the inclusion of zinc along with bone cement which induces osteoblast formation at the localized area and eventually new bone formation happens. Another material was developed where Co-Cr alloy was coated with bioactive glass by a process of enameling. The coated alloy was immersed in SBF for 30 days to observe the deposition of HAP on its surface which eventually increases the bioactivity of the material. This has also had wide applications in the tissue engineering field [55].
Another new fabrication was created using a porous scaffold containing foam-like bioglass and poly (lactide-co-glycolide) PLGA. The scaffold showed high microporosity and also the material was favorable for cell adhesion and hence this scaffold was widely applied in tissue engineering [56]. Another researcher [57] also developed a scaffold containing BCP and agarose gel. He analyzed the compression behavior of the scaffold and found that agarose improved the property of BCP by imparting elasticity, ductility, and toughness to the material. Hence, this scaffold could be used in the tissue engineering process. Another researcher [58] too prepared a scaffold comprising of two proteins namely bovine serum albumin and alpha casein by a cold gelation process. The developed scaffold can perform better in its porosity, cytotoxicity, and swelling ratio and the pH changes unalters the scaffold performance. An Indian researcher [59] also prepared bone grafts containing fibrin functionalized graphene oxide (FGO) and graphene oxide (GO) on to which HAP was grown by wet precipitation method. An
Another Indian scientist team [60] prepared a bone substitute with the incorporation of the extracts of
The widely used dental implants are known for their unique characteristics. Recently, novel dental implants incorporated with herbal composites were evaluated by research scientists and revealed abundant evidence on such materials. These implants developed enhanced bone healing and strengthens the bone, accelerates osseointegration, inhibits osteopenia, and inhibits inflammation. These novel implants allow good biocompatibility, viability and shorten the rehabilitation time for the patients. The application of herbal composite inclusion in dentistry and its applications has a greater potential to improve the success rate of dental implant and allows the implications of biotechnology in implant dentistry.
Head-related transfer functions (HRTFs) describe the filtering of the acoustic field produced by a sound source arriving at the listener’s ear. The filtering is the effect of the interaction of the sound field with the listener’s anatomy and has various properties. First, the incoming sound wave arrives at the ipsilateral pinna, i.e., the ear closer to the sound source, and then at the contralateral ear, i.e., the ear away from the sound source. This time difference between ipsilateral and contralateral ear is usually described as the interaural time difference (ITD). Second, larger anatomical structures, i.e., torso, shoulders and head, affect frequencies up to 3 kHz in a comparatively trivial way. As the listener’s torso and head shadow the sound wave arriving at the contralateral ear, interaural level differences (ILDs) arise. Third, the incoming sound is filtered in a complex way by the shape of the listener’s pinnae. These monaural time-frequency-filtering effects become especially important for higher frequency regions (above approximately 4 kHz) and sound directions inducing the same ITDs and ILDs [1, 2, 3, 4, 5, 6]. Humans have learned to interpret this acoustic filtering to span an auditory space as an internal model of their natural environment [7]. Because the pinna shape is unique for every person, HRTFs are considered listener-specific [8, 9, 10], similar to a fingerprint [1, 2, 3, 4, 5, 6]. With an individually fitted HRTF dataset, it is possible for a person to perceive sounds (in a virtual environment) via headphones as if the sounds would originate from their (physical) position around the listener.
Both interaural and monaural features for a single sound direction can be represented by a binaural HRTF pair [11]. In signal processing terms, a binaural HRTF pair can be described as
where
There are several options to set a specific coordinate system to systematically describe directions for HRTFs. From the physical perspective, the
Coordinate systems typically used in the HRTF acquisition and representation. The dashed line represents the interaural axis, and the arrow represents the viewing direction. (a) Spherical coordinate system with the azimuth and elevation angles. (b) Simple interaural-polar coordinate system with the lateral and polar angles obtained by rotation the poles of the spherical system. (c) Modified interaural-polar coordinate system with the lateral and polar angles corresponding to the azimuth angle in the horizontal plane and the elevation angle in the median plane.
The understanding of these coordinate systems is important because state-of-the-art acquisitions and representations of HRTFs utilise those systems. For example, Figure 2 shows HRTFs along the Frankfurt and the median plane. These various coordinate systems are used in HRTF visualisation, in various HRTF-related software packages such as the SOFA toolbox [15], and in auditory modelling, e.g., the Auditory Modelling Toolbox (AMT) [16, 17].
HRTF magnitude spectra for the listeners (a) NH236 and (b) NH257, both from the ARI database [
HRTF acquisition can be classified into three categories: acoustic measurement, numerical calculation, and personalisation [18].
The acoustic measurement is traditionally designed as the measurement of the impulse response between source and receiver in an anechoic or semianechoic chamber, describing the transmission path from a sound source to the ear [11, 19]. A comprehensive review of the established state-of-the-art acoustic techniques to measure HRTFs can be found in [20]. Thus, in this chapter, Section 3, we only briefly provide an overview of the traditional acoustic HRTF measurement approaches, highlight some of their differences and new trends and focus on the requirements for the acoustic measurement.
Numerical HRTF calculation simulates the acoustic measurement by considering a 3D representation of the listener’s geometry and the positions of multiple external sound sources, for which the generated sound pressure at the entrance of the ear canal is calculated. This technique has become more popular and is the main focus of this chapter. To this end, in Section 4, we provide an overview of the principles of various numerical calculation approaches including a comparison of the mentioned methods.
Personalisation of HRTFs describes the process of adapting an existing set of generic data guided by listener-specific information, either with the help of objective or subjective personalisation method. The objective personalisation has been approached from two different domains: the geometric domain, in which listener-specific anthropometric data are measured and used to personalise a generic geometric model from which HRTFs are then simulated; or the spectral domain, in which a generic HRTF set is directly personalised based on listener-specific information. Examples for personalisation approaches include utilising frequency scaling [21], parametric modelling of peaks and notches [22], active shape modelling (ASM) [23], principal component analysis (PCA) in both geometric [24] and spectral domains [25, 26, 27, 28, 29], multiple regression analysis [30], independent component analysis (ICA) [31], large deformation diffeomorphic metric mapping (LDDMM) [25, 32], local neighbourhood mapping [33], neural networks [34, 35, 36, 37, 38, 39, 40, 41] and linear combination of HRTFs [42]. Despite many efforts worldwide [43, 44, 45, 46], the link between the morphology and HRTFs is not fully understood yet, mostly because of the high dimensionality of the problem. Most recent tools for studying that link are rooted in aligning high-resolution pinna representations to target representations facilitated with parametric pinna models [47, 48].
In the subjective personalisation, listeners are confronted with several sets of HRTFs and an algorithm (usually based on the evaluation of localisation errors, i.e., the difference between perceived and actual sound-source location) adapts the HRTF sets aiming at converging at listener-specific HRTFs [9, 49]. For an educated guess for the initial sets, anthropometric data can be used to pre-scale the HRTF sets, or the HRTF sets can be pre-selected via psychoacoustic models [50]. Clustering of the HRTF sets can further improve the relevance and reduce the duration of the personalisation procedure [49, 51].
All these methods aim at providing a specific quality in terms of acoustic and psychoacoustic properties. In the following section, we describe the acoustic properties and psychoacoustic requirements for human HRTFs, both of which lay the base for HRTF acquisition. Then, we briefly describe the most important requirements for the acoustic HRTF measurement, complementing the work of Li and Peissig [20]. Finally, we describe approaches for numeric HRTF calculation in greater detail.
In this section, we describe the acoustic properties of HRTFs and relate them to psychophysical properties of human hearing with the goal to derive the minimum requirements for sufficiently accurate HRTF acquisition by means of perception. We analyse spectral, temporal and spatial aspects of HRTFs and consider contributions of distinct parts of the human body to these aspects.
Humans can hear frequencies roughly between 20 Hz and 20 kHz, with frequencies at the lower end being perceived as vibrations or creaks, and with the upper end decreasing with age and duration of noise exposure [52]. From the psychoacoustic perspective, frequencies down to 90 Hz contribute to sound lateralisation, i.e., localisation on the interaural axis within the head [53], and up to 16 kHz to sound localisation, i.e., localisation outside the head [54], defining the smallest frequency range for the HRTF acquisition. Figure 2 shows the amplitude spectra of a binaural HRTF pair of two listeners. For each listener, the left and right columns show HRTFs of the left and right ear, respectively. The top row shows the HRTFs along the median, i.e., for the lateral angle of zero, from the front, via up, to the back. The bottom row shows the HRTFs along the Frankfurt plane, i.e., the horizontal plane located at the eye level. Figure 2 demonstrates that HRTFs vary across ears, frequency, sound-source positions and listeners. The bottom panels emphasise the difference between ipsilateral and contralateral ear, showing the dynamic range, especially for frequencies higher than 6 kHz.
Assuming the propagation medium is air and a sonic speed of 340 m/s, the human hearing frequency range translates to wavelengths approximately between 1.7 cm and 17 m, resulting in different body parts affecting HRTFs in different frequency regions. The reflections of the torso create spatial-frequency modulations in the range of up to 3 kHz [1]. This effect can be observed in the top row of Figure 2, in the form of elevation-dependent spectral modulations along the median plane [55, 56]. Another contribution comes from the head, which shadows frequencies above 1 kHz. This effect can be observed in both rows of Figure 2, with large changes in the spectra beginning at around 1 kHz [57]. A large contribution is that of the pinna: The resonances and reflections within the pinna geometry create spectral peaks and notches, respectively, in frequencies above 4 kHz [54]. This effect can be observed in the bottom row of Figure 2.
From the perceptual perspective, the quality of these HRTF spectral profiles is important in many processes involved in spatial hearing. For example, sound-localisation performance deteriorates when these spectral profiles are disturbed by means of introducing spectral ripples [58], reducing the number of frequency channels [59] or spectral smoothing [60]. From the acoustic perspective, these spectral profiles show modulation depths of up to 50 dB [11], defining the required dynamic range in the process of HRTF acquisition.
The temporal aspects of HRTF acquisition are shown in Figure 3 as the head-related impulse responses (HRIRs), i.e., HRTFs in the time domain, of the same listeners as in Figure 2. There are a few things to consider. First, the minimum length of the measurement is bounded by the length of the HRIRs. Their amplitude decays within the first 5 ms, setting the requirement for the room impulse response during the measurements [61]. After the 5 ms, the HRIRs decay below 50 dB, setting the requirement on the broadband signal-to-noise ratio (SNR) of the measurements. Further, because of the human sensitivity to interaural disparities, HRTF acquisition also requires an interaural temporal synchronisation. While sound sources placed in the median plane cause an ITD of zero (theoretically, reached only for identical path lengths to the two ears), just small deviations from the median plane cause potentially perceivable non-zero ITDs. Human listeners can detect ITDs being as small as 10 μs [53, 62], defining the interaural temporal precision required in the HRTF acquisition process. The ITD increases with the lateral angle of the sound source, reaching its extreme values for sources placed near the interaural axis [63, 64]. The largest ITD depends on the distance between the listener’s two ears, mostly being defined by the listener’s head width and depth [65], reaching ITDs of up to ±800 μs. That ITD range translates to the sound’s time of arrival (TOA) at an ear varying in the range of 1.6 ms, which needs to be considered in HRTF measurement by providing sufficient temporal space in the resulting impulse response.
HRTF log-magnitudes in time domain along the eye-level horizontal plane for the same listeners as in
HRTFs are continuous functions in space, even though, they are traditionally acquired for a finite set of spatial positions. From the
HRTFs are listener-specific, i.e., they vary among the listeners [21]. The reasons for that inter-individual variation are usually rooted in listener-specific morphology of the head and ears. For example, the variation in the head width of approximately ±2 cm across the population causes variation in the largest ITD in the range of ±80 μs [89]. Figure 4 shows HRTF-relevant parts of the human body, where Figure 4a shows rough measures of the body and Figure 4b shows areas of the pinna responsible for the distinct spectral features in higher frequencies. The width and depth of head and torso have a large effect on HRTFs in the lower frequencies. The inter-individual variation in the pinnae geometry causes variations in HRTFs in frequencies above 4 kHz, with listener-specific differences of up to 20 dB [11]. The inter-individual variation in the HRTFs is rather complex because the pinna is a complex biological structure—small variations in geometry (in the range of millimetres) may cause drastic changes in HRTFs [90] along the vertical planes in high frequencies [11], see Figure 2. However, not all pinna regions affect HRTFs equally [91]. Basically, the convex curvatures of the pinnae contribute to focusing the incoming sound waves towards the entry of the ear canals, comparable to a satellite dish. Figure 4b shows the anatomical areas important for localisation of sounds [48, 56, 88, 92, 93]. Currently, the description of the pinna geometry is not a trivial task. Pinnae have been described by means of anthropometric data stored in various data collections, e.g., [67, 69, 89, 94, 95, 96]. While the parameters used in these data collections do not seem to completely describe a pinna geometry from scratch, recent efforts aim at parametric pinna models able to generate non-pathological pinna geometries for arbitrary listeners [47, 48]. Such models describe the pinna geometry by means of various control points placed on the surface of a template pinna geometry. Figure 5 shows two examples of the implementation of such models. In Figure 5a, the pinna geometry is parametrised with the help of Beziér curves, i.e., polynomials within a spatial boundary [47]. Figure 5b shows a different approach; here, the parameterisation of the pinna is utilised with control points that move proximal local areas [48]. These parametric pinna models represent a step towards understanding the link between HRTFs and specific anatomical regions of the pinnae, and provide potential to synthesise large datasets of pinnae, e.g., in order to provide data for machine-learning algorithms.
HRTF-relevant parts of the human body. (a): Head and torso represented with simple shapes based on [
Examples of parametric pinna models. (a): Model from [
In addition to the geometry, skin and hair may have an impact on HRTFs [97, 98] because of their direction-dependent absorption of the acoustic energy, especially at high frequencies. However, recent studies have shown that hair does not influence the localisation performance, but rather the perception of timbre instead [95, 99, 100, 101].
The principle of an acoustic HRTF measurement relies on the system identification of the HRTF considered as a linear and time-invariant system. Here, an HRTF describes the propagation path between a microphone and a loudspeaker. Because of the binaural synchronisation, HRTFs are measured simultaneously at the two ears. The measurements are commonly performed for many source positions because of the required high spatial resolution. Recently, the details of the acoustic measurements, including a comprehensive list of HRTF measurement sites has been reviewed [20]. Thus, we only briefly introduce the basics and focus on the most recent advances in the acoustic HRTF measurement.
Typically, two omnidirectional microphones are placed in both ear canals, and the loudspeakers are arranged around the listener, ideally, with the number of loudspeakers corresponding to the number of HRTF positions to be measured. Figure 6 shows two examples of measurement setups of various complexity: In Figure 6a, the listener is located on a turntable and moves within a fixed near-complete circular loudspeaker array. Figure 6b shows a similar approach with a near-complete spherical loudspeaker array, and Figure 6c shows the placement of a microphone in the ear canal so that it is membrane lines up with the entrance of the ear canal. Actually, it does not matter whether the microphones or loudspeakers are placed in the ear canal—this approach of ‘reciprocity’ is usually facilitated in numeric HRTF calculations (Section 4.4). However, setups with loudspeakers in the ears [102] lack signal-to-noise ratio (SNR) as the amplitude of the source signal needs to be low enough to not harm the listener, making the setup impractical for experiments. With the microphones in the ears, the most simple setups consist of a single loudspeaker moved around the listener [103]. Unfortunately, such setups lead to a long measurement duration for a dense set of HRTF positions. With the increasing availability of multichannel sound interfaces and adequate electroacoustic equipment, over the decades, the number of actually used loudspeakers increased. Setups with only a single loudspeaker moving around the listener have been replaced by setups with loudspeaker arcs surrounding the listener. In those setups, the listener sits on a turntable and either the listener (e.g., Figure 6a) or the loudspeaker arc is rotated [89, 104].
(a) Example of an HRTF measurement setup with mechanical rotation required. Listener sits on a chair (mounted on a turntable) surrounded by a loudspeaker arc (22 loudspeakers ranging from −30 to 210° in 5°-steps). A head-tracker mounted on the head of the listener tracks head movements, triggering the need for measurement repetition in case of too large movements. (b) Example of more recent HRTF setups. 91 loudspeakers are mounted in a near-complete spherical array reducing the total measurement duration. (c) Example for a microphone placement in an HRTF measurement. Note the closed ear canal and the head-tracker sensor.
Recent approaches follow one of two different directions; On the one hand, generic and individual HRTFs are measured with a growing number of loudspeakers used in specialised facilities [67, 95]. Some even with such a large amount of loudspeakers that the listener is rotated for a few discrete positions, and post-processing algorithms interpolate between HRTF directions, e.g., the setup in Figure 6b. On the other hand, user-friendly individual HRTF measurement approaches are suggested, showing a trend towards decreasing the complexity of the measurement setup and using widely available equipment. In these approaches, only a single speaker is used and the listener is asked to move the head until a dense setup of HRTF directions can be obtained. These measurements enable simple systems to be used at home [105, 106], in which a head-tracking system records the listener’s head movements in real time and adapts the measured spatial HRTF grid. Head-above-torso orientations have to be considered additionally [100], but they reduce the complexity of the measurement setup and enable using widely available equipment, e.g., a commercially available VR headset and one arbitrary loudspeaker, in regular rooms, thus increasing the user-friendliness for setups [105].
Most of those recent approaches consider spatially discrete positions of the listener and/or the loudspeakers. In order to tackle the trade-off between high spatial resolution and long measurement duration, other recent advances have been made towards spatially continuous measurement approaches [107, 108, 109]. These approaches enable the measuring of all directions around the listener for a single elevation within less than 4 minutes [110]. Certainly, an advantage of such an approach is the access to the spatially continuous information, which is important especially for frontal HRTF directions. With more and more silent turntables and swivelled chairs, achieving a high SNR is not a big issue. Most recent approaches related to the spatially continuous measurement utilise Kalman filters to acquire system parameters representing HRTFs, and thus speed up the HRTF measurement in a multi-channel setup [111]. Compared to spatially discrete approaches, the spatially continuous method can achieve accuracy within a spectral error of 2 dB [109].
The requirements of the room are not rigorous: In principle, the measurement room does not have to be perfectly anechoic, but it has to fulfil some requirements regarding size and reverberation time. Room modes may exist below 500 Hz as they can be neglected in that frequency range [1]. Acceptable measurement results can be obtained as long as the first room reflection arises after 5 ms such that the measured room impulse responses can be truncated without truncating the HRIRs. Medium and large surfaces, i.e., the mount of the loudspeakers, the loudspeaker arc, the turntable, listener seat, etc., can potentially cause acoustical reflections overlapping with the direct sound path within the first 5 ms of the HRTF. These reflections are usually damped, e.g., by covering the speakers in absorption material. Before the measurement, the listener’s head has to be aligned in the measurement setup, adjusting the ears to the interaural axis of the system and the head to the Frankfurt plane. This alignment can be supported by, e.g., a laser system. The orientation and position of the listener’s head should be monitored throughout the measurement procedure in order to detect listener’s unwanted movements or position drifts. This helps when having to repeat potentially corrupted measurements.
The loudspeakers used for the measurements need to show a fast impulse response decay; fast enough to not interfere with the temporal characteristics of the HRTFs. This can be achieved by using loudspeaker drivers with light membranes, simple electric processing and no acoustic feedback such as a bass-reflex system. The acoustic short-circuit usually limits the lower frequency range of the loudspeakers, and multidriver systems are a common solution to that problem. In order to achieve a spatially compact acoustic source in a multidriver system, it is common to use coaxial loudspeaker drivers with an omnidirectional directivity pattern in HRTF measurement systems [112].
The placement of the microphones can also be an issue. Early setups used an open ear canal where the microphones were positioned close to the eardrum [11]. However, the effect of the ear canal does not seem to be direction-dependent, and its consideration in the measurement introduces technical difficulties and a large measurement variance [19, 113, 114]. Nowadays, the microphones are usually placed at the entrance of the ear canal which is acoustically blocked [11, 20]. Blocking the ear canal can be achieved by using microphones enclosed in earplugs made from foam or silicone or by wrapping the microphone in skin-friendly tape before inserting it. Note that such a measurement captures all directional-dependent features of the acoustic filtering by the outer ear, however, the directional-independent filtering by the ear canal is not captured. All cables from the microphone have to be flexible enough to minimise their effect on the acoustics within the pinna—one way is to lead the cable through the incisura intertragica and secure it with tape on the cheek, see Figure 6c.
In general, system identification can be performed with a variety of excitation signals. While previously Golay codes or other broadband signals have been used [115], more recently, the multiple exponential sweep method (MESM) [112] has been established and further improved [116], enabling fast HRTF measurement at high SNRs, reducing the discomfort for the listener. Still because of the imperfections in the electro-acoustic setup, a reference measurement is required to estimate the basis of the measurement without the effect of the listener, i.e., to estimate
Figure 7 shows measurement grids of three exemplary setups and one measurement grid of a simulation setup. Figure 7a and b correspond to the measurement setups in Figure 6a and b. In these setups, not every loudspeaker plays a stimulus at every position around the listener. An extreme case is a loudspeaker positioned at
Four examples of spatial HRTF grid resolutions. (a) Almost spherical loudspeaker arc with moving listener, see also
The repeatability of the measurement is an important issue. Within a single laboratory, changes in the room conditions such as temperature and humidity, as well as changes in the setup such as the ageing of the equipment may compromise the repeatability of the HRTF measurement [11, 20]. When comparing the HRTFs measurement across the labs, differences in the setups play also a role. In inter-laboratory and inter-method HRTF measurement comparison obtained for the same artificial head, severe ITD variations of up to 200
Once the HRTFs have been measured for all source positions, post-processing needs to be done before the HRTFs are ready to be used. First, in order to account for acoustic artefacts caused by the measurement room, a frequency-dependent windowing function is usually applied truncating the HRIRs [100, 117, 118]. Second, the measured HRIRs are equalised by the impulse response obtained from the reference measurements, i.e., with the microphone placed at the centre of the coordinate system with the listener absent. This equalisation can be either free-field or diffuse-field. For the free-field equalisation, the reference measurement is required only for the frontal direction (0° azimuth, 0° elevation) [54], whereas for the diffuse-field equalisation, the reference measurement is the root mean square (RMS) impulse response of all directions [75], and the results are commonly denoted as directional transfer functions (DFT) [119]. Third, in most common rooms and even in (semi)anechoic rooms, reflections (or room modes) cause artefacts below 400 Hz, confounding the free-field property of HRTFs. Additionally, most loudspeakers used in the measurement are not able to reproduce low frequencies with sufficient power. Since the listener’s anthropometry has a small effect on HRTFs in the low-frequency range, HRTFs can be extrapolated towards lower frequencies with a constant magnitude and linear phase [20, 117]. Further post-processing steps may include spectral smoothing to account for listener position inaccuracies [60, 120] or adding a fractional delay to account for temperature changes followed by onset changes of the time signals [100].
The availability of acoustical HRTF measurements was a big step towards personalised binaural audio and virtual reality experience. However, even a fast or continuous measurement method requires the listener to sit still for a few minutes [104, 110, 112] in a specialised lab facility. Recent advances have been made towards both large-scale high-resolution and small-scale at-home easy-to-use solutions, providing HRTF acquisition to a large audience. Still, the imperfections in the electro-acoustic equipment set drawbacks of the acoustic measurement. Here, recent advances in the numeric calculations of the HRTFs can provide an interesting alternative.
Generally, the calculation of HRTFs simulates the effects of the pinna, head and torso on the sound field at the eardrum. The goal is to numerically obtain the sound pressure at the two ears for a given set of frequencies and spatial positions. There are many methods to simulate wave propagation [121]. When applied to the HRTF calculation, all of the methods require a geometric representation of head and pinnae as input. For an accurate set of HRTFs, an exact 3D representation of the geometry, especially that of the pinnae with all their crests and folds, is of utmost importance [90]. The 3D geometry is represented using a discrete and finite set of elements, further denoted as ‘mesh’. A mesh is a representation of the region of interest (ROI), i.e., the object’s volume and surface, with the help of simple geometric elements. In most applications, the faces of these elements are assumed to be flat, which in turn explains the preference for triangular faces because they are always flat and therefore have one unique normal vector. This is not always the case for other shapes, e.g., quadrilaterals.
The requirements on the mesh have to consider geometrical as well as acoustical aspects. From the acoustic perspective, a typical rule of thumb for numerical calculation requires the average edge length (AEL) of elements to be at least a sixth of the smallest wavelength [122], which corresponds to an AEL of 3.5 mm for frequencies up to 16 kHz. However, in order to describe the pinna geometry sufficiently accurate, the average edge length (AEL) of the elements in the mesh needs to be around 1 mm, independently of the calculation method [90]. Some numerical calculation algorithms are, in general, more efficient and stable if the geometries are represented locally with elements of similar sizes and as regular as possible, e.g., almost equilateral triangles. To this end, the mesh may undergo a so-called
Pinna meshes represented by various AELs [
Interestingly, only the pinna regions contributing to the HRTF (compare Figure 4b) require to be accurately represented [56] and the remainder of the geometry can be more roughly modelled. This applies especially to the head, torso and neck, which can be represented by larger elements. These anatomical parts can additionally be approximated by simple geometric shapes, e.g., a sphere for the head, a cylinder for the neck and a rectangular cuboid or an ellipsoid representing the torso [65], see e.g., Figure 4a. To emphasise the sophisticated direction dependency of the pinna, Figure 9 shows the calculated sound pressure distribution over the surface of the pinna. This simulation is calculated by defining one element in the centre of the ear canal as a sound source and evaluating the resulting sound pressure field at the vertices of the rest of the geometry; the procedure is explained thoroughly in Section 4.4.
Magnitude of the sound pressure calculated for each element of the surface for a 13-kHz sound source placed in the ear canal. Note the high dynamic range containing peaks (red) and notches (blue) in the distribution pattern in the area of the pinna.
The geometry can be captured via numerous approaches [124]: a laser scan [125], medical imaging techniques such as magnetic resonance imaging (MRI) [69, 126] and computer tomography (CT) [90], or photogrammetric reconstruction [127]. Laser, MRI and CT scans yield high-resolution meshes offering a small geometric error, but in turn, they need a special equipment. The laser scans are based on line-of-sight propagation and are able to measure short distances with an accuracy of up to 0.01 mm. The downside of line-of-sight propagation is that the manifolds of the pinnae are not easy to capture. In the medical imaging approaches, different downsides arise; acquiring the pinnae geometry via MRI is not a trivial process because they are flattened by the head support. This leads to two separate MRI measurements of each ear. The anatomy is then captured in ‘slices’ that can be stitched together in the postprocessing rather easily. The CT captures the anatomy in a similar way, but due to the high radiation exposure, such scans are usually not done with human subjects but with (silicone) mouldings of the listener’s ear. The overall procedure may take more time than an acoustic HRTF measurement and require the listener to either manufacture a moulding or meeting rather specific criteria for the scanning equipment (e.g., no tattoos, piercings, or implants). As an alternative, recent advances have been made for more widely applicable approaches such as photogrammetry [23, 128]. Photogrammetry is not only non-invasive but also can be done with widely available equipment, e.g., a smartphone or digital camera, without having the listener to travel to a specialised facility. In a nutshell, the photogrammetrical approach works as follows: a set of photographs from different directions is made for each ear [127, 129], the so-called
Simulations of acoustics require the information about the acoustic properties of the simulated objects. The HRTFs can be simulated with the 3D geometry represented as fully reflective, i.e., all surfaces having infinite acoustic impedance. With respect to localisation performance, only a small
In order to calculate HRTFs with sufficient spectral accuracy, the number of elements needs to be in the range of several tens of thousands, which might be important for the requirements of the computational power. Such large numerical problems usually require large amount of memory being in the range of Gigabytes. Nevertheless, the calculation time may reach a few days, especially when calculating HRTFs for many frequencies with high-resolution meshes. Note that if the used algorithm calculates HRTFs for each frequency independently, the calculations can be performed in parallel, and computer clusters can be used. This reduces the calculation time to a few hours for HRTFs the full hearing range and a mesh of several tens of thousands of elements.
All the algorithms for numerical HRTF calculation are based on the propagation of sound waves in the free field around a scattering object (also “scatterer”), usually described by the Helmholtz equation
where
In order to solve the Helmholtz equation for a given scatterer, boundary conditions are necessary. The
where
with
For the calculation of HRTFs, the Helmholtz equation can be solved numerically by means of various approaches, which are based on a discretisation of the exterior domain
The finite-element method (FEM) solves the Helmholtz equation, Eq. (2), considering the scattering object or the domain around it as a volume [132]. Figure 10 shows an example of a finite (domain) volume
2D representation of meshes used in FEM. The elements are uniformly distributed and fitted to the boundary of the domain
Secondly, the unknown pressure
of so-called ansatz functions
where
and
In general, the unknown coefficients
When calculating HRTFs, the space around the scatterer is assumed to be continuous and infinite; in practice, this space has to be discretised and truncated to a finite domain by inserting a virtual boundary. When applied to the calculation of HRTFs, a virtual boundary of the (now finite) domain
The FEM has been widely used in HRTF calculations [137, 138, 139, 140, 141] and yields similar results to acoustical HRTF measurements with spectral magnitude errors of approximately 1 dB [137, 141]. The downside, however, is the need to model 3D volumes around the head, resulting in models of a high number of elements, having a strong impact on the calculation duration.
A similar approach as the FEM can also be followed in the time domain. By using a short sound burst in the time domain as an input signal, the HRTFs within a wide frequency range can be calculated at once. This approach is called the finite-difference time-domain (FDTD) method [142] and can be derived by solving the wave equation in the time domain
where
defining the number of cells the sound propagates per time step. Typically, in order to obtain stable HRTF calculations, the Courant number is
Figure 11 shows a 2D representation of a mesh used in the FDTD method. Note that because the mesh needs to consist of evenly spaced elements, most of the objects cannot be represented accurately and a sampling error is introduced at the boundary surface
2D representation of meshes used in the FDTD method. Note that in this representation, the object surface
Because of the additional sampling errors for irregular domains, recent advances have been made towards using quasi-cartesian grids [148], dynamically choosing grid resolutions [149], or towards the finite-volume method (FVTD), which is based on energy conservation and dissipation of the system as a whole and uses the integral formulation of the FDTD [150]. One solution approach there is to adaptively sample the grid at the boundary and introduce unstructured or fitted cells [151, 152]. A thorough comparison between FEM, FDTD and FVTD methods is available in [153].
In fact, the FDTD method has been widely applied to HRTF calculations [145, 146, 154, 155], and it certainly offers the advantage of calculating broadband HRTFs while not introducing additional computational cost when multiple inputs or outputs are used. However, because of the complex geometry of the pinnae, a submillimetre sampling grid is required, resulting in the need for a delicate preprocessing.
The boundary element method (BEM) is based on a special set of test functions in the weak formulation of the Helmholtz equation Eq. (3), namely the Green’s function
where
where
In comparison with the other two methods, the BEM has the advantage that only the
2D representation of a BEM mesh. Note that only the boundary of the surface
In order to solve a BEM problem, the BIE is discretized and solved by using methods such as the Galerkin, collocation or Nyström [157, 158, 159], all with the common goal of yielding a linear system of equations.
For the Galerkin method, the unknown pressure is approximated by a linear combination of ansatz functions as in Eq. (4). The BIE is again multiplied with a set of test functions (similar to the test functions
and
Another commonly used approach especially used in engineering is collocation with constant elements, i.e., the sound field is assumed to be constant on each element of the mesh, and the BIE is solved at the midpoints
The BIE is solved for a given set of frequencies and the solutions
The discretisation of just the surface introduces additional challenges. First, the Green’s function becomes singular at the boundary where
In order to efficiently deal with such large systems, the BEM can be coupled with methods speeding up matrix–vector multiplications, such as the fast-multipole method (FMM) [163] or
is found. This approximation has two advantages: the local expansions
Although the Helmholtz equation for external problems has a unique solution at all frequencies, the BIE has uniqueness problems at certain critical frequencies [159, 167]. Thus, to avoid numerical problems, the BEM needs to be stabilised at these frequencies, e.g., by using the Burton-Miller method [167]. BEM has been widely used to calculate HRTFs [165, 168, 169, 170, 171] analysing the process from various perspectives. When applied to an accurate and high-resolution representation of the pinna geometry, BEM can yield similar results to the acoustic HRTF measurements by means of sound localisation performance [101, 172].
In principle, in order to calculate an HRTF set, the Helmholtz equation needs to be solved for every source position
Helmholtz’ reciprocity theorem states that switching source and receiver positions do not affect the observed sound pressure. When applied to HRTF calculations, virtual loudspeakers are placed in the entrance of the ear canal (replacing the virtual microphones) and the many simulated sound sources are represented by many virtual microphones (replacing the many virtual loudspeakers around the listener). By doing so, the computationally expensive part of the BEM, i.e., solving a linear system of equations to calculate the sound pressure at the surface, needs to be done only twice, namely once for each ear. Subsequently, the sound pressure at positions around the head can be calculated fairly easy and efficiently.
In more detail, assume that a point source with strength
The reciprocal sound source can be modelled by vibrating elements
where
Note that this equation is calculated after a discretisation, and because
Reciprocity, combined with FMM-coupled BEM has been applied to calculate HRTFs, enabling calculations for a large spatial HRTF set within a few hours even on a standard desktop computer [172].
Over decades, HRTFs have been collected and stored in databases. Such databases are important for educational aspects, training of neural network algorithms [34, 37] and further research [23, 25, 26, 27, 28, 173]. While in the early HRTF research days, HRTFs have been stored by each lab in a different format, since 2015, the spatially oriented format for acoustics (SOFA) is available to store HRTFs in a flexible but well-described way facilitating an easy exchange between the labs and applications. SOFA is a standard of the Audio Engineering Society under the name AES69. SOFA provides a uniform description of spatially oriented acoustic data such as HRTFs, spatial room impulse responses, and directivities [15].
When it comes to anthropometric data, unfortunately, there is currently no common format to specify and exchange anthropometric data. This is partially because currently, it is not known, which data are important. Some laboratories use the CIPIC parameters [89], some have extended them [174], and others have created whole new sets of parameters [128, 175]. An overview of currently used anthropometric parameters can be found in [176]. The development of parametric pinna models may shed light on the relevance of parameters needed to be stored in the future. The listener’s geometry can also be stored in non-parametric representations such as meshes and point clouds of listener’s ears and head. To this end, typical 3D dataset formats are used, e.g., OBJ, PLY or STL. These formats are widely used in computer graphics and thus easily accessible by many corresponding applications. A large collection of HRTF databases stored in SOFA, with some of them combined with meshes stored in OBJ, PLY and STL files is available at the SOFA website.1
When HRTFs are obtained, there is strong demand to evaluate their quality. This is especially interesting when comparing the results from numerical HRTF calculations. The evaluations can be performed at various levels: geometrical, acoustical and perceptive. The evaluation at the geometric level can be done by comparing the deviation between two meshes of the pinna and representing the deviation as the Hausdorff distance [177]. The evaluation at the acoustic level can be done by calculating the spectral distortion
where
With a specialised measurement setup, acoustic HRTF measurements can be done within a few minutes. Still, such setups are expensive and require the listener to sit or stand still for the whole measurement duration. The requirement of specialised components has been limiting the popularity of the acoustic methods. Recent advances, however, have been made by integrating head-movement tracking in systems to be used at home, especially since the commercialisation of VR headsets. These advances provide an easy-to-use measurement setup, but still need investigation on how many and which measurement positions are crucial to acquire a sufficient measurement grid for perceptually valid HRTFs.
With the availability of numerical HRTF calculations, the acquisition of personalised HRTFs has undergone significant advances. While the acoustic HRTF measurement still remains the reference acquisition method, numerical HRTF calculation paves the road towards personalised HRTFs available for a wide audience. The most widely used approaches, FEM, FDTD, BEM and BEM coupled with the FMM, when applied under optimal conditions, can yield acoustically and perceptually valid results.
Machine learning and neural networks gain increasing popularity and, in the future, may even further push the usability of numerical HRTF calculations. For example, neural networks might be able to support the photogrammetric mesh acquisition or even estimate the HRTFs directly from listener-specific anthropometric data such as photographs. Further improvements in terms of efficiency, accuracy and precision are still ongoing subject of research.
Despite the clear definition when it comes to storing an HRTF data set by means of SOFA, a similar definition for the description of anthropometric data is still not available. This might be rooted in our poor understanding of the importance of parts of the pinna and its contribution to the HRTF. Here, a clear goal is to better understand the anthropometry and its relation with HRTFs. All this future work heads into the direction of expanding the access to personalised HRTFs enabling their availability for everyone.
This work was supported by the Austrian Research Promotion Agency (FFG, project ‘softpinna’ 871263) and the European Union (EU, project ‘SONICOM’ 101017743, RIA action of Horizon 2020). We thank Harald Ziegelwanger for visualising the sound pressure in Figure 9.
The authors declare no conflict of interest.
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Just like the identification of the marker chromosome or the identification of the complex karyotypes is important in clinics for the evaluation of the patient prognosis as well as the treatment response, needless to say; fluorescence in situ hybridization (FISH) is the most suitable and rapid method in the above-mentioned situations. It gives chance to the rapid analysis of chromosomal aneuploidies in dividing and non-dividing cells. 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He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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Then take a masters degree in science in Germany (Animal breeding). Take a doctorate in animal science at the UANL.",institutionString:null,institution:{name:"Universidad Autónoma de Nuevo León",country:{name:"Mexico"}}},{id:"309250",title:"Dr.",name:"Miguel",middleName:null,surname:"Quaresma",slug:"miguel-quaresma",fullName:"Miguel Quaresma",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/309250/images/9059_n.jpg",biography:"Miguel Nuno Pinheiro Quaresma was born on May 26, 1974 in Dili, Timor Island. He is married with two children: a boy and a girl, and he is a resident in Vila Real, Portugal. He graduated in Veterinary Medicine in August 1998 and obtained his Ph.D. degree in Veterinary Sciences -Clinical Area in February 2015, both from the University of Trás-os-Montes e Alto Douro. He is currently enrolled in the Alternative Residency of the European College of Animal Reproduction. 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He teaches diverse courses in the field of Animal Reproduction and he is the Director of the Veterinary Farm. He also participates in academic postgraduate activities at the Veterinary Faculty of Murcia University, Spain. His research areas include animal physiology, physiology and biotechnology of reproduction either in males or females, the study of gametes under in vitro conditions and the use of ultrasound as a complement to physiological studies and development of applied biotechnologies. Routinely, he supervises students preparing their doctoral, master thesis or final degree projects.",institutionString:null,institution:{name:"Valencia Catholic University Saint Vincent Martyr",country:{name:"Spain"}}},{id:"309529",title:"Dr.",name:"Albert",middleName:null,surname:"Rizvanov",slug:"albert-rizvanov",fullName:"Albert Rizvanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/309529/images/9189_n.jpg",biography:'Albert A. Rizvanov is a Professor and Director of the Center for Precision and Regenerative Medicine at the Institute of Fundamental Medicine and Biology, Kazan Federal University (KFU), Russia. He is the Head of the Center of Excellence “Regenerative Medicine” and Vice-Director of Strategic Academic Unit \\"Translational 7P Medicine\\". Albert completed his Ph.D. at the University of Nevada, Reno, USA and Dr.Sci. at KFU. He is a corresponding member of the Tatarstan Academy of Sciences, Russian Federation. Albert is an author of more than 300 peer-reviewed journal articles and 22 patents. He has supervised 11 Ph.D. and 2 Dr.Sci. dissertations. Albert is the Head of the Dissertation Committee on Biochemistry, Microbiology, and Genetics at KFU.\nORCID https://orcid.org/0000-0002-9427-5739\nWebsite https://kpfu.ru/Albert.Rizvanov?p_lang=2',institutionString:"Kazan Federal University",institution:{name:"Kazan Federal University",country:{name:"Russia"}}},{id:"210551",title:"Dr.",name:"Arbab",middleName:null,surname:"Sikandar",slug:"arbab-sikandar",fullName:"Arbab Sikandar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210551/images/system/210551.jpg",biography:"Dr. Arbab Sikandar, PhD, M. Phil, DVM was born on April 05, 1981. He is currently working at the College of Veterinary & Animal Sciences as an Assistant Professor. He previously worked as a lecturer at the same University. \nHe is a Member/Secretory of Ethics committee (No. CVAS-9377 dated 18-04-18), Member of the QEC committee CVAS, Jhang (Regr/Gen/69/873, dated 26-10-2017), Member, Board of studies of Department of Basic Sciences (No. CVAS. 2851 Dated. 12-04-13, and No. CVAS, 9024 dated 20/11/17), Member of Academic Committee, CVAS, Jhang (No. CVAS/2004, Dated, 25-08-12), Member of the technical committee (No. CVAS/ 4085, dated 20,03, 2010 till 2016).\n\nDr. Arbab Sikandar contributed in five days hands-on-training on Histopathology at the Department of Pathology, UVAS from 12-16 June 2017. He received a Certificate of appreciation for contributions for Popularization of Science and Technology in the Society on 17-11-15. He was the resource person in the lecture series- ‘scientific writing’ at the Department of Anatomy and Histology, UVAS, Lahore on 29th October 2015. He won a full fellowship as a principal candidate for the year 2015 in the field of Agriculture, EICA, Egypt with ref. to the Notification No. 12(11) ACS/Egypt/2014 from 10 July 2015 to 25th September 2015.; he received a grant of Rs. 55000/- as research incentives from Director, Advanced Studies and Research, UVAS, Lahore upon publications of research papers in IF Journals (DR/215, dated 19-5-2014.. He obtained his PhD by winning a HEC Pakistan indigenous Scholarship, ‘Ph.D. fellowship for 5000 scholars – Phase II’ (2av1-147), 17-6/HEC/HRD/IS-II/12, November 15, 2012. \n\nDr. Sikandar is a member of numerous societies: Registered Veterinary Medical Practitioner (life member) and Registered Veterinary Medical Faculty of Pakistan Veterinary Medical Council. The Registration code of PVMC is RVMP/4298 and RVMF/ 0102.; Life member of the University of Veterinary and Animal Sciences, Lahore, Alumni Association with S# 664, dated: 6-4-12. ; Member 'Vets Care Organization Pakistan” with Reference No. VCO-605-149, dated 05-04-06. :Member 'Vet Crescent” (Society of Animal Health and Production), UVAS, Lahore.",institutionString:"University of Veterinary & Animal Science",institution:{name:"University of Veterinary and Animal Sciences",country:{name:"Pakistan"}}},{id:"311663",title:"Dr.",name:"Prasanna",middleName:null,surname:"Pal",slug:"prasanna-pal",fullName:"Prasanna Pal",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311663/images/13261_n.jpg",biography:null,institutionString:null,institution:{name:"National Dairy Research Institute",country:{name:"India"}}},{id:"202192",title:"Dr.",name:"Catrin",middleName:null,surname:"Rutland",slug:"catrin-rutland",fullName:"Catrin Rutland",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202192/images/system/202192.png",biography:"Catrin Rutland is an Associate Professor of Anatomy and Developmental Genetics at the University of Nottingham, UK. She obtained a BSc from the University of Derby, England, a master’s degree from Technische Universität München, Germany, and a Ph.D. from the University of Nottingham. She undertook a post-doctoral research fellowship in the School of Medicine before accepting tenure in Veterinary Medicine and Science. Dr. Rutland also obtained an MMedSci (Medical Education) and a Postgraduate Certificate in Higher Education (PGCHE). She is the author of more than sixty peer-reviewed journal articles, twelve books/book chapters, and more than 100 research abstracts in cardiovascular biology and oncology. She is a board member of the European Association of Veterinary Anatomists, Fellow of the Anatomical Society, and Senior Fellow of the Higher Education Academy. Dr. Rutland has also written popular science books for the public. https://orcid.org/0000-0002-2009-4898. www.nottingham.ac.uk/vet/people/catrin.rutland",institutionString:null,institution:{name:"University of Nottingham",country:{name:"United Kingdom"}}},{id:"283315",title:"Prof.",name:"Samir",middleName:null,surname:"El-Gendy",slug:"samir-el-gendy",fullName:"Samir El-Gendy",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRduYQAS/Profile_Picture_1606215849748",biography:"Samir El-Gendy is a Professor of anatomy and embryology at the faculty of veterinary medicine, Alexandria University, Egypt. Samir obtained his PhD in veterinary science in 2007 from the faculty of veterinary medicine, Alexandria University and has been a professor since 2017. Samir is an author on 24 articles at Scopus and 12 articles within local journals and 2 books/book chapters. His research focuses on applied anatomy, imaging techniques and computed tomography. Samir worked as a member of different local projects on E-learning and he is a board member of the African Association of Veterinary Anatomists and of anatomy societies and as an associated author at local and international journals. Orcid: https://orcid.org/0000-0002-6180-389X",institutionString:null,institution:{name:"Alexandria University",country:{name:"Egypt"}}},{id:"246149",title:"Dr.",name:"Valentina",middleName:null,surname:"Kubale",slug:"valentina-kubale",fullName:"Valentina Kubale",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246149/images/system/246149.jpg",biography:"Valentina Kubale is Associate Professor of Veterinary Medicine at the Veterinary Faculty, University of Ljubljana, Slovenia. Since graduating from the Veterinary faculty she obtained her PhD in 2007, performed collaboration with the Department of Pharmacology, University of Copenhagen, Denmark. She continued as a post-doctoral fellow at the University of Copenhagen with a Lundbeck foundation fellowship. She is the editor of three books and author/coauthor of 23 articles in peer-reviewed scientific journals, 16 book chapters, and 68 communications at scientific congresses. Since 2008 she has been the Editor Assistant for the Slovenian Veterinary Research journal. She is a member of Slovenian Biochemical Society, The Endocrine Society, European Association of Veterinary Anatomists and Society for Laboratory Animals, where she is board member.",institutionString:"University of Ljubljana",institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"258334",title:"Dr.",name:"Carlos Eduardo",middleName:null,surname:"Fonseca-Alves",slug:"carlos-eduardo-fonseca-alves",fullName:"Carlos Eduardo Fonseca-Alves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/258334/images/system/258334.jpg",biography:"Dr. Fonseca-Alves earned his DVM from Federal University of Goias – UFG in 2008. He completed an internship in small animal internal medicine at UPIS university in 2011, earned his MSc in 2013 and PhD in 2015 both in Veterinary Medicine at Sao Paulo State University – UNESP. Dr. Fonseca-Alves currently serves as an Assistant Professor at Paulista University – UNIP teaching small animal internal medicine.",institutionString:null,institution:{name:"Universidade Paulista",country:{name:"Brazil"}}},{id:"245306",title:"Dr.",name:"María Luz",middleName:null,surname:"Garcia Pardo",slug:"maria-luz-garcia-pardo",fullName:"María Luz Garcia Pardo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/245306/images/system/245306.png",biography:"María de la Luz García Pardo is an agricultural engineer from Universitat Politècnica de València, Spain. She has a Ph.D. in Animal Genetics. Currently, she is a lecturer at the Agrofood Technology Department of Miguel Hernández University, Spain. Her research is focused on genetics and reproduction in rabbits. The major goal of her research is the genetics of litter size through novel methods such as selection by the environmental sensibility of litter size, with forays into the field of animal welfare by analysing the impact on the susceptibility to diseases and stress of the does. Details of her publications can be found at https://orcid.org/0000-0001-9504-8290.",institutionString:null,institution:{name:"Miguel Hernandez University",country:{name:"Spain"}}},{id:"350704",title:"M.Sc.",name:"Camila",middleName:"Silva Costa",surname:"Ferreira",slug:"camila-ferreira",fullName:"Camila Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/350704/images/17280_n.jpg",biography:"Graduated in Veterinary Medicine at the Fluminense Federal University, specialist in Equine Reproduction at the Brazilian Veterinary Institute (IBVET) and Master in Clinical Veterinary Medicine and Animal Reproduction at the Fluminense Federal University. She has experience in analyzing zootechnical indices in dairy cattle and organizing events related to Veterinary Medicine through extension grants. I have experience in the field of diagnostic imaging and animal reproduction in veterinary medicine through monitoring and scientific initiation scholarships. I worked at the Equus Central Reproduction Equine located in Santo Antônio de Jesus – BA in the 2016/2017 breeding season. I am currently a doctoral student with a scholarship from CAPES of the Postgraduate Program in Veterinary Medicine (Pathology and Clinical Sciences) at the Federal Rural University of Rio de Janeiro (UFRRJ) with a research project with an emphasis on equine endometritis.",institutionString:null,institution:null},{id:"41319",title:"Prof.",name:"Lung-Kwang",middleName:null,surname:"Pan",slug:"lung-kwang-pan",fullName:"Lung-Kwang Pan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41319/images/84_n.jpg",biography:null,institutionString:null,institution:null},{id:"125292",title:"Dr.",name:"Katy",middleName:null,surname:"Satué Ambrojo",slug:"katy-satue-ambrojo",fullName:"Katy Satué Ambrojo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/125292/images/system/125292.jpeg",biography:"Katy Satué Ambrojo received her Veterinary Medicine degree, Master degree in Equine Technology and doctorate in Veterinary Medicine from the Faculty of Veterinary, CEU-Cardenal Herrera University in Valencia, Spain.Dr. Satué is accredited as a Private University Doctor Professor, Doctor Assistant, and Contracted Doctor by AVAP (Agència Valenciana d'Avaluació i Prospectiva) and currently, as a full professor by ANECA (since January 2022). To date, Katy has taught 22 years in the Department of Animal Medicine and Surgery at the CEU-Cardenal Herrera University in undergraduate courses in Veterinary Medicine (General Pathology, integrated into the Applied Basis of Veterinary Medicine module of the 2nd year, Clinical Equine I of 3rd year, and Equine Clinic II of 4th year). Dr. Satué research activity is in the field of Endocrinology, Hematology, Biochemistry, and Immunology in the Spanish Purebred mare. She has directed 5 Doctoral Theses and 5 Diplomas of Advanced Studies, and participated in 11 research projects as a collaborating researcher. She has written 2 books and 14 book chapters in international publishers related to the area, and 68 scientific publications in international journals. Dr. Satué has attended 63 congresses, participating with 132 communications in international congresses and 19 in national congresses related to the area. Dr. Satué is a scientific reviewer for various prestigious international journals such as Animals, American Journal of Obstetrics and Gynecology, Veterinary Clinical Pathology, Journal of Equine Veterinary Science, Reproduction in Domestic Animals, Research Veterinary Science, Brazilian Journal of Medical and Biological Research, Livestock Production Science and Theriogenology, among others. Since 2014 she has been responsible for the Clinical Analysis Laboratory of the CEU-Cardenal Herrera University Veterinary Clinical Hospital.",institutionString:null,institution:null},{id:"201721",title:"Dr.",name:"Beatrice",middleName:null,surname:"Funiciello",slug:"beatrice-funiciello",fullName:"Beatrice Funiciello",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/201721/images/11089_n.jpg",biography:"Graduated from the University of Milan in 2011, my post-graduate education included CertAVP modules mainly on equines (dermatology and internal medicine) and a few on small animal (dermatology and anaesthesia) at the University of Liverpool. After a general CertAVP (2015) I gained the designated Certificate in Veterinary Dermatology (2017) after taking the synoptic examination and then applied for the RCVS ADvanced Practitioner status. After that, I completed the Postgraduate Diploma in Veterinary Professional Studies at the University of Liverpool (2018). My main area of work is cross-species veterinary dermatology.",institutionString:null,institution:null},{id:"291226",title:"Dr.",name:"Monica",middleName:null,surname:"Cassel",slug:"monica-cassel",fullName:"Monica Cassel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/291226/images/8232_n.jpg",biography:'Degree in Biological Sciences at the Federal University of Mato Grosso with scholarship for Scientific Initiation by FAPEMAT (2008/1) and CNPq (2008/2-2009/2): Project \\"Histological evidence of reproductive activity in lizards of the Manso region, Chapada dos Guimarães, Mato Grosso, Brazil\\". Master\\\'s degree in Ecology and Biodiversity Conservation at Federal University of Mato Grosso with a scholarship by CAPES/REUNI program: Project \\"Reproductive biology of Melanorivulus punctatus\\". PhD\\\'s degree in Science (Cell and Tissue Biology Area) \n at University of Sao Paulo with scholarship granted by FAPESP; Project \\"Development of morphofunctional changes in ovary of Astyanax altiparanae Garutti & Britski, 2000 (Teleostei, Characidae)\\". She has experience in Reproduction of vertebrates and Morphology, with emphasis in Cellular Biology and Histology. She is currently a teacher in the medium / technical level courses at IFMT-Alta Floresta, as well as in the Bachelor\\\'s degree in Animal Science and in the Bachelor\\\'s degree in Business.',institutionString:null,institution:null},{id:"442807",title:"Dr.",name:"Busani",middleName:null,surname:"Moyo",slug:"busani-moyo",fullName:"Busani Moyo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Gwanda State University",country:{name:"Zimbabwe"}}},{id:"439435",title:"Dr.",name:"Feda S.",middleName:null,surname:"Aljaser",slug:"feda-s.-aljaser",fullName:"Feda S. Aljaser",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"423023",title:"Dr.",name:"Yosra",middleName:null,surname:"Soltan",slug:"yosra-soltan",fullName:"Yosra Soltan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Alexandria University",country:{name:"Egypt"}}},{id:"349788",title:"Dr.",name:"Florencia Nery",middleName:null,surname:"Sompie",slug:"florencia-nery-sompie",fullName:"Florencia Nery Sompie",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sam Ratulangi University",country:{name:"Indonesia"}}},{id:"428600",title:"MSc.",name:"Adriana",middleName:null,surname:"García-Alarcón",slug:"adriana-garcia-alarcon",fullName:"Adriana García-Alarcón",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Autonomous University of Mexico",country:{name:"Mexico"}}},{id:"428599",title:"MSc.",name:"Gabino",middleName:null,surname:"De La Rosa-Cruz",slug:"gabino-de-la-rosa-cruz",fullName:"Gabino De La Rosa-Cruz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Autonomous University of Mexico",country:{name:"Mexico"}}},{id:"428601",title:"MSc.",name:"Juan Carlos",middleName:null,surname:"Campuzano-Caballero",slug:"juan-carlos-campuzano-caballero",fullName:"Juan Carlos Campuzano-Caballero",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Autonomous University of Mexico",country:{name:"Mexico"}}}]}},subseries:{item:{id:"7",type:"subseries",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11403,editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",slug:"slawomir-wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",biography:"Professor Sławomir Wilczyński, Head of the Chair of Department of Basic Biomedical Sciences, Faculty of Pharmaceutical Sciences, Medical University of Silesia in Katowice, Poland. 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Editor-in-chief of the journal in the field of aesthetic medicine and dermatology - Aesthetica.",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,series:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343"},editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",slug:"alexandros-tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",slug:"lulu-wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:"Shenzhen Technology University",institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda R.",middleName:"R.",surname:"Gharieb",slug:"reda-r.-gharieb",fullName:"Reda R. 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