Comparison of descriptives and internal consistencies of the unidimensional perceptual features. Calculations are based on the total sample (music and speech group,
\\n\\n
IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\\n\\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
\\n\\nBiomedical Engineering, ISSN 2631-5343
\\n\\nInfectious Diseases, ISSN 2631-6188
\\n\\nPhysiology (Coming Soon)
\\n\\nDentistry (Coming Soon)
\\n\\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\\n\\nNote: Edited in October 2021
\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/132"}},components:[{type:"htmlEditorComponent",content:'With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\n\nLaunching 2021
\n\nArtificial Intelligence, ISSN 2633-1403
\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
\n\nPhysiology (Coming Soon)
\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 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:"9134",leadTitle:null,fullTitle:"Recent Advances in Digital System Diagnosis and Management of Healthcare",title:"Recent Advances in Digital System Diagnosis and Management of Healthcare",subtitle:null,reviewType:"peer-reviewed",abstract:"Technologically supported healthcare management is beginning to take center stage as advances occur in many aspects of healthcare, involving big data, artificial intelligence, and improved user interfaces. This volume provides a perspective on a number of such advances, ranging from homecare with remote network support and primary homecare to telemedicine application for pediatric cardiology. A special section with chapters on Clinical Decision Support Systems (CDSS) addresses topics in improved human interfaces, intelligent support for better quality home and institutional care, effective big data visualization for decision-makers, and gathering data from multiple sources to support the battle against resistant bacteria.",isbn:"978-1-78985-882-2",printIsbn:"978-1-78985-881-5",pdfIsbn:"978-1-78985-604-0",doi:"10.5772/intechopen.83130",price:119,priceEur:129,priceUsd:155,slug:"recent-advances-in-digital-system-diagnosis-and-management-of-healthcare",numberOfPages:148,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"ff00a5718f23cb880b7337b1c36b5434",bookSignature:"Kamran Sartipi and Thierry Edoh",publishedDate:"February 3rd 2021",coverURL:"https://cdn.intechopen.com/books/images_new/9134.jpg",numberOfDownloads:5069,numberOfWosCitations:0,numberOfCrossrefCitations:1,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:5,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:6,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 15th 2019",dateEndSecondStepPublish:"September 4th 2019",dateEndThirdStepPublish:"November 3rd 2019",dateEndFourthStepPublish:"January 22nd 2020",dateEndFifthStepPublish:"March 22nd 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"29601",title:"Dr.",name:"Kamran",middleName:null,surname:"Sartipi",slug:"kamran-sartipi",fullName:"Kamran Sartipi",profilePictureURL:"https://mts.intechopen.com/storage/users/29601/images/system/29601.jpeg",biography:"Dr. Kamran Sartipi is a faculty member in the Department of Computer Science at East Carolina University, Greenville, North Carolina, and an adjunct faculty member in the Information Systems at McMaster University, Ontario, Canada. Dr. Sartipi’s education includes degrees in Electrical and Computer Engineering, and Computer Science and Software Engineering. His research activities are interdisciplinary including different aspects of intelligent decision systems through behavior pattern extraction, artificial intelligence, and big data analytics. Dr. Sartipi has long-term expertise in data analytics, knowledge engineering, intelligent decision systems, and software engineering, including successful applications in medical informatics and cybersecurity. He has more than eighty scientific publications in peer-reviewed journals and conferences. He has international research collaborations and trained several Ph.D. and master’s students in interdisciplinary fields.",institutionString:"East Carolina University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"East Carolina University",institutionURL:null,country:{name:"United States of America"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"234682",title:"Ph.D.",name:"Thierry",middleName:null,surname:"Edoh",slug:"thierry-edoh",fullName:"Thierry Edoh",profilePictureURL:"https://mts.intechopen.com/storage/users/234682/images/system/234682.png",biography:"Thierry Oscar Edoh is an affiliated researcher at the University of Bonn, North Rhine-Westphalia, Germany (Drug Regulatory Affairs Program); visiting associate lecturer at the Institute of Mathematics and Physics (IMSP), University Abomey-Calavi, Benin, Africa; and visiting lecturer at the University Institute of Technology (IUT), Benin, Africa. Previously, he was an affiliated researcher in the Department of Applied Software Engineering at the Technical University of Munich, Germany. \n\nHe received his diploma in Computer Sciences from the Technical University of Munich, Germany, and a Ph.D. in computer science from the German Federal Army University (Bundeswehr University), Munich, where he worked for several years on the improvement of rural health care provision and access to healthcare in developing countries using ITC systems. \nHe has performed postdoctoral research works at the University of Bonn.",institutionString:"University of Bonn",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Bonn",institutionURL:null,country:{name:"Germany"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1015",title:"Healthcare Informatics",slug:"healthcare-informatics"}],chapters:[{id:"68526",title:"The Evolution of Elderly Telehealth and Health Informatics",doi:"10.5772/intechopen.88416",slug:"the-evolution-of-elderly-telehealth-and-health-informatics",totalDownloads:1146,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"Many elderly individuals experience memory loss and often dementia as they age. This causes problems for the elderly due to diminished skills and increase in medical problems and natural decline. The Veterans Health Administration (VHA) introduced a national home telehealth program, Care Coordination/Home Telehealth (CCHT). Its purpose was to coordinate the care of veteran patients with chronic conditions and avoid their unnecessary admission to long-term institutional care. Such programs are cost-effective. Long-term care insurance companies are likely to cover these services. Home care and nursing home corporations are following the VHA’s lead. We have recently witnessed significant advances in technology. Internet and mobile applications have opened a new world, providing information and opportunities for individuals to learn more information about illness and at a much faster rate. Smart home technology has evolved. Elderly patients often encounter difficulties using these technologies. Despite the advances in telehealth and telemedicine and the evolution of the technology, many individuals cannot afford the treatment or the technology. These same individuals and families are part of the digital divide, and they have not embraced the new technology. Federal programs have been developed and implemented to help this portion of the population.",signatures:"Joseph P. Lyons, Kimberly Watson and Angela Massacci",downloadPdfUrl:"/chapter/pdf-download/68526",previewPdfUrl:"/chapter/pdf-preview/68526",authors:[{id:"300756",title:"Dr.",name:"Joseph P.",surname:"Lyons",slug:"joseph-p.-lyons",fullName:"Joseph P. Lyons"},{id:"300761",title:"MSc.",name:"Kimberly",surname:"Watson",slug:"kimberly-watson",fullName:"Kimberly Watson"},{id:"306168",title:"Dr.",name:"Angela",surname:"Perez-Massacci",slug:"angela-perez-massacci",fullName:"Angela Perez-Massacci"}],corrections:null},{id:"68405",title:"Actual as well as Future Technologies and Noninvasive Devices for Optimal Management of Diabetes Mellitus and Chronic Heart Failure",doi:"10.5772/intechopen.87983",slug:"actual-as-well-as-future-technologies-and-noninvasive-devices-for-optimal-management-of-diabetes-mel",totalDownloads:312,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In recent years, several technological innovations have become part of the daily lives of patients suffered from chronic diseases. It is the case for diabetes mellitus and chronic heart failure with noninvasive glucose sensors, intelligent insulin pumps, artificial pancreas, telemedicine, and artificial intelligence for an optimal management. A review of the literature dedicated to these technologies and devices supports the efficacy of the latter. Mainly, these technologies have shown a beneficial effect on diabetes or chronic heart failure management with mainly improvement for these two diseases of patient ownership of the disease; patient adherence to therapeutic and hygiene-dietary measures; the management of comorbidities (hypertension, weight, dyslipidemia); and at least, good patient receptivity and accountability. Especially, the emergence of these technologies in the daily lives of these patients suffered from chronic disease has led to an improvement of the quality of life for patients. Nevertheless, the magnitude of its effects remains to date debatable or to be consolidated, especially with the variation in patients’ characteristics and methods of experimentation and in terms of medical and economic objectives.",signatures:"Emmanuel Andrès, Nathalie Jeandidier, Samy Talha, Abrar-Ahmad Zulfiqar, Laurent Meyer, Noel Lorenzo Villalba, Thibault Bahougne, Mohamed Hajjam and Amir Hajjam El Hassani",downloadPdfUrl:"/chapter/pdf-download/68405",previewPdfUrl:"/chapter/pdf-preview/68405",authors:[{id:"143493",title:"Prof.",name:"Emmanuel",surname:"Andrès",slug:"emmanuel-andres",fullName:"Emmanuel Andrès"}],corrections:null},{id:"73175",title:"Primary Health-Care Service Delivery and Accessibility in the Digital Age",doi:"10.5772/intechopen.93347",slug:"primary-health-care-service-delivery-and-accessibility-in-the-digital-age",totalDownloads:377,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The primary care is within a health-care system, the first contact and main point for people requiring health and medical care. Patients requiring specialized health and medical care are directed to the appropriate specialists by a general physician (GP) who coordinates the needed specialist care. GPs base their decisions partially on patient-centered information and partially on the results of medical examinations. Many health-IT systems for primary health care are available today. Their first aims are to assist GPs in their daily duties and the patient in collecting his medical data and to self-manage his conditions. IT systems enabling the patient to collect accurate information on his condition to self-manage his condition provide accurate patient-centric data, which shows the potential to outperform patient-centered information, which in turn is based on the patient’s personal feeling and perception. Patient-centered information are biased. Beyond providing patient-centric information, health-IT systems can facilitate access to health-care services, increase the quality, efficiency, and effectiveness of health-care services, and can contribute to reducing medical expenses. This chapter aims to paint down the global trend of health-IT systems and the supporting technology. The chapter will further present some existing health-IT systems and discuss their role in the health-care accessibility, particularly in rural regions.",signatures:"Thierry Edoh",downloadPdfUrl:"/chapter/pdf-download/73175",previewPdfUrl:"/chapter/pdf-preview/73175",authors:[{id:"234682",title:"Ph.D.",name:"Thierry",surname:"Edoh",slug:"thierry-edoh",fullName:"Thierry Edoh"}],corrections:null},{id:"70359",title:"Telemedicine Network in Pediatric Cardiology: The Case of Tuscany Region in Italy",doi:"10.5772/intechopen.90382",slug:"telemedicine-network-in-pediatric-cardiology-the-case-of-tuscany-region-in-italy",totalDownloads:741,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Four years ago, a telemedicine project in diagnosis and care of congenital cardiac malformations was developed in Tuscany interconnecting the Heart Hospital of Gabriele Monasterio Tuscany Foundation (FTGM) in Massa with main clinical centers around the region. Both live and store-and-forward tele-echocardiography were implemented, while the FTGM medical record system was applied for collaborative reporting. Mobile medical-grade carts, equipped with videoconferencing and computer units, were installed at main neonatology/pediatric centers throughout the Tuscany region. Today, 13 hospitals are connected to the network, while the MEYER Pediatric University Hospital (MEYER) in Firenze has recently adhered to the project, as HUB center jointly with FTGM, so enabling H24 telemedicine service in pediatric cardiology throughout the region. So far, more than 200 patients were diagnosed and followed by telemedicine.",signatures:"Alessandro Taddei, Pierluigi Festa, Fabrizio Conforti, Giuseppe Santoro, Gianluca Rocchi and Luciano Ciucci",downloadPdfUrl:"/chapter/pdf-download/70359",previewPdfUrl:"/chapter/pdf-preview/70359",authors:[{id:"305545",title:"Dr.",name:"Alessandro",surname:"Taddei",slug:"alessandro-taddei",fullName:"Alessandro Taddei"},{id:"305959",title:"Dr.",name:"Luciano",surname:"Ciucci",slug:"luciano-ciucci",fullName:"Luciano Ciucci"},{id:"305960",title:"Dr.",name:"Gianluca",surname:"Rocchi",slug:"gianluca-rocchi",fullName:"Gianluca Rocchi"},{id:"313107",title:"Dr.",name:"Fabrizio",surname:"Conforti",slug:"fabrizio-conforti",fullName:"Fabrizio Conforti"},{id:"313108",title:"Dr.",name:"Pierluigi",surname:"Festa",slug:"pierluigi-festa",fullName:"Pierluigi Festa"},{id:"313124",title:"Dr.",name:"Giuseppe",surname:"Santoro",slug:"giuseppe-santoro",fullName:"Giuseppe Santoro"}],corrections:null},{id:"71939",title:"Owning Attention: Applying Human Factors Principles to Support Clinical Decision Support",doi:"10.5772/intechopen.92291",slug:"owning-attention-applying-human-factors-principles-to-support-clinical-decision-support",totalDownloads:601,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"In the best examples, clinical decision support (CDS) systems guide clinician decision-making and actions, prevent errors, improve quality, reduce costs, save time, and promote the use of evidence-based recommendations. However, the potential solution that CDS represents are limited by problems associated with improper design, implementation, and local customization. Despite an emphasis on electronic health record usability, little progress has been made to protect end-users from inadequately designed workflows and unnecessary interruptions. Intelligent and personalized design creates an opportunity to tailor CDS not just at the patient level but specific to the disease condition, provider experience, and available resources at the healthcare system level. This chapter leverages the Five Rights of CDS framework to demonstrate the application of human factors engineering principles and emerging trends to optimize data analytics, usability, workflow, and design.",signatures:"Robin Littlejohn, Ronald Romero Barrientos, Christian Boxley and Kristen Miller",downloadPdfUrl:"/chapter/pdf-download/71939",previewPdfUrl:"/chapter/pdf-preview/71939",authors:[{id:"301003",title:"Ph.D.",name:"Kristen",surname:"Miller",slug:"kristen-miller",fullName:"Kristen Miller"},{id:"301013",title:"Ms.",name:"Robin",surname:"Littlejohn",slug:"robin-littlejohn",fullName:"Robin Littlejohn"},{id:"307329",title:"Mr.",name:"Ronald",surname:"Romero Barrientos",slug:"ronald-romero-barrientos",fullName:"Ronald Romero Barrientos"},{id:"307330",title:"Mr.",name:"Christian",surname:"Boxley",slug:"christian-boxley",fullName:"Christian Boxley"}],corrections:null},{id:"69527",title:"An Intelligent Clinical Decision Support System for Assessing the Needs of a Long-Term Care Plan",doi:"10.5772/intechopen.89663",slug:"an-intelligent-clinical-decision-support-system-for-assessing-the-needs-of-a-long-term-care-plan",totalDownloads:611,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"With the global aging population, providing effective long-term care has been promoted and emphasized for reducing the hospitalizations of the elderly and the care burden to hospitals and governments. Under the scheme of Long-term Care Project 2.0 (LTCP 2.0), initiated in Taiwan, two types of long-term care services, i.e., institutional care and home care, are provided for the elderly with chronic diseases and disabilities, according to their personality, living environment and health situation. Due to the increasing emphasis on the quality of life in recent years, the elderly expect long-term care service providers (LCSP) to provide the best quality of care (QoC). Such healthcare must be safe, effective, timely, efficiently, diversified and up-to-date. Instead of supporting basic activities in daily living, LCSPs have changed their goals to formulate elderly-centered care plans in an accurate, time-efficient and cost-effective manner. In order to ensure the quality of the care services, an intelligent clinical decision support system (ICDSS) is proposed for care managers to improve their efficiency and effectiveness in assessing the long-term care needs of the elderly. In the ICDSS, artificial intelligence (AI) techniques are adopted to distinguish and formulate personalized long-term care plans by retrieving relevant knowledge from past similar records.",signatures:"Paul Kai Yuet Siu, Valerie Tang, King Lun Choy, Hoi Yan Lam and George To Sum Ho",downloadPdfUrl:"/chapter/pdf-download/69527",previewPdfUrl:"/chapter/pdf-preview/69527",authors:[{id:"296597",title:"Dr.",name:"K.L.",surname:"Choy",slug:"k.l.-choy",fullName:"K.L. Choy"},{id:"296613",title:"Dr.",name:"H.Y.",surname:"Lam",slug:"h.y.-lam",fullName:"H.Y. Lam"},{id:"305062",title:"Ms.",name:"Valerie",surname:"Tang",slug:"valerie-tang",fullName:"Valerie Tang"},{id:"305098",title:"Dr.",name:"G.T.S.",surname:"Ho",slug:"g.t.s.-ho",fullName:"G.T.S. Ho"},{id:"305099",title:"Mr.",name:"Paul K.Y.",surname:"Siu",slug:"paul-k.y.-siu",fullName:"Paul K.Y. Siu"}],corrections:null},{id:"70326",title:"A Systematic Review of Knowledge Visualization Approaches Using Big Data Methodology for Clinical Decision Support",doi:"10.5772/intechopen.90266",slug:"a-systematic-review-of-knowledge-visualization-approaches-using-big-data-methodology-for-clinical-de",totalDownloads:665,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"This chapter reports on results from a systematic review of peer-reviewed studies related to big data knowledge visualization for clinical decision support (CDS). The aims were to identify and synthesize sources of big data in knowledge visualization, identify visualization interactivity approaches for CDS, and summarize outcomes. Searches were conducted via PubMed, Embase, Ebscohost, CINAHL, Medline, Web of Science, and IEEE Xplore in April 2019, using search terms representing concepts of: big data, knowledge visualization, and clinical decision support. A Google Scholar gray literature search was also conducted. All references were screened for eligibility. Our review returned 3252 references, with 17 studies remaining after screening. Data were extracted and coded from these studies and analyzed using a PICOS framework. The most common audience intended for the studies was healthcare providers (n = 16); the most common source of big data was electronic health records (EHRs) (n = 12), followed by microbiology/pathology laboratory data (n = 8). The most common intervention type was some form of analysis platform/tool (n = 7). We identified and classified studies by visualization type, user intent, big data platforms and tools used, big data analytics methods, and outcomes from big data knowledge visualization of CDS applications.",signatures:"Mehrdad Roham, Anait R. Gabrielyan and Norm Archer",downloadPdfUrl:"/chapter/pdf-download/70326",previewPdfUrl:"/chapter/pdf-preview/70326",authors:[{id:"36663",title:"Prof.",name:"Norman",surname:"Archer",slug:"norman-archer",fullName:"Norman Archer"},{id:"300760",title:"Dr.",name:"Anait",surname:"Gabrielyan",slug:"anait-gabrielyan",fullName:"Anait Gabrielyan"},{id:"308660",title:"Dr.",name:"Mehrdad",surname:"Roham",slug:"mehrdad-roham",fullName:"Mehrdad Roham"}],corrections:null},{id:"71316",title:"WASPSS: A Clinical Decision Support System for Antimicrobial Stewardship",doi:"10.5772/intechopen.91648",slug:"waspss-a-clinical-decision-support-system-for-antimicrobial-stewardship",totalDownloads:617,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The increase of infections caused by resistant bacteria has become one of the major health-care problems worldwide. The creation of multidisciplinary teams dedicated to the implementation of antimicrobial stewardship programmes (ASPs) is encouraged by all clinical institutions to cope with this problem. In this chapter, we describe the Wise Antimicrobial Stewardship Program Support System (WASPSS), a CDSS focused on providing support for ASP teams. WASPSS gathers the required information from other hospital systems in order to provide decision support in antimicrobial stewardship from both patient-centered and global perspectives. To achieve this, it combines business intelligence techniques with a rule-based inference engine to integrate the data and knowledge required in this scenario. The system provides functions such as alerts, recommendations, antimicrobial prescription support and global surveillance. Furthermore, it includes experimental modules for improving the adoption of clinical guidelines and applying prediction models related with antimicrobial resistance. All these functionalities are provided through a multi-user web interface, personalized for each role of the ASP team.",signatures:"Bernardo Cánovas Segura, Antonio Morales, Jose M. Juarez, Manuel Campos and Francisco Palacios",downloadPdfUrl:"/chapter/pdf-download/71316",previewPdfUrl:"/chapter/pdf-preview/71316",authors:[{id:"304477",title:"Ph.D.",name:"Bernardo",surname:"Canovas Segura",slug:"bernardo-canovas-segura",fullName:"Bernardo Canovas Segura"},{id:"309732",title:"Dr.",name:"Antonio",surname:"Morales",slug:"antonio-morales",fullName:"Antonio Morales"},{id:"309733",title:"Prof.",name:"Manuel",surname:"Campos",slug:"manuel-campos",fullName:"Manuel Campos"},{id:"309734",title:"Prof.",name:"Jose M.",surname:"Juarez",slug:"jose-m.-juarez",fullName:"Jose M. Juarez"},{id:"309736",title:"Dr.",name:"Francisco",surname:"Palacios",slug:"francisco-palacios",fullName:"Francisco Palacios"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6653",title:"eHealth",subtitle:"Making Health Care Smarter",isOpenForSubmission:!1,hash:"c65db68c389c911ae57b1181b3e0db07",slug:"ehealth-making-health-care-smarter",bookSignature:"Thomas F. Heston",coverURL:"https://cdn.intechopen.com/books/images_new/6653.jpg",editedByType:"Edited by",editors:[{id:"217926",title:"Dr.",name:"Thomas F.",surname:"Heston",slug:"thomas-f.-heston",fullName:"Thomas F. 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\r\n\r\n\tDemands for the more comfortable, faster, cheaper, more reliable, and more accurate way for medical diagnosis and intervention has been pushing the shift of researcher's interest from conventional medical procedures that based on biochemical and immunological methods to proposed medical procedures based on physical methods.
\r\n\r\n\tThis book mainly aims to discus on physical aspects of medical technology, procedures, or devices. This book welcomes topics on how physical methods substitute conventional methods for medical diagnosis and intervention and also proposed methods and their clinical trial reports as evidence of their performance.
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He received the B.S. in agro-meteorology from Bogor Agricultural University, in 1988, M.S. degrees in physics from University of Indonesia, in 1998, and Ph.D. degree in physics from Bandung Technology University, Bandung, in 2005.\n\nSince 1997, he is a resident lecturer of Physics Physics Department, Bogor Agricultural University. From 2007 to 2011, He is Physics Head of Department, Bogor Agricultural University. From 2011, He is Head of Material Physics Laboratory, Physics Department, Bogor Agricultural University. He is the author of 16 Scopus indexed journal articles and a book chapter. His research interests include sensors engineering, semiconductor device physics and new material characterization, and ferroelectrics. 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He received B.S. degree in agriculture engineering from Bogor Agricultural University in 2005, M.S. degree in software engineering from Bandung Technology University in 2008, and Ph.D. Degree in human nutrition from Bogor Agricultural University 2018.\nFrom 2008 to 2013, he was a researcher in Binus Foundation. Since 2013, He is an IT Consultant for Child Growth and Development Cohort Study, Bogor, West Java, Indonesia, and Researcher for Physics Department, Bogor Agricultural University. He is the author of 4 Scopus indexed proceedings articles and a book chapter, and editorial assistant for a book. 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The first total LeFort I osteotomy was performed by Wassmund in 1927 for correction of the skeletal open bite [2]. In spite of all the advancements made in the field of orthognathic surgery, a variety of complications are documented [3]. These include maxillary sinusitis, loss of tooth vitality, sensory nerve morbidity, aseptic necrosis, vascular complications (i.e., arteriovenous fistulae or hemorrhage) nasal septum deviation, unfavorable fractures of the skull base and pterygoid plates, ophthalmic complications (including blindness) malpositioning, nonunion, maxilla instability, and relapse [4].
\nExcessive bleeding has been reported as a common complication of LeFort osteotomies. The incidence of life‐threatening hemorrhage in maxillary osteotomies is reported in approximately 1% [5]. The descending palatine artery is the most common source for mild to moderate bleeding during LeFort I osteotomy and delayed bleeding afterward. The descending palatine artery damage may occur during the medial wall osteotomy. Injury to the descending palatine artery during LeFort I osteotomy can be minimized by limiting the osteotomy to 30 mm posterior to the piriform rim in females and to 35 mm in males[6]. In maxillary superior repositioning, bone removal around the descending palatine artery is a common cause of vascular injury. If the surgeon encounters the descending palatine artery, it should be cauterized. The internal maxillary artery is the most frequently cited source of massive hemorrhage [7]. Meticulous placement of the curved osteotome in the pterygomaxillary junction is important to avoid injury to the internal maxillary artery and its branches. Turvey and Fonseca reported that the main trunk of the maxillary artery was most vulnerable to the damage within the pterygopalatine fossa in the lateral position and they recommended angling the posterior lateral maxillary osteotomy downward to avoid damaging the artery [8]. Packing is suggested as the first attempt to tamponade the hemorrhage. In delayed bleeding after LeFort I osteotomy, the surgeon should reopen surgical site and move the maxilla downward to find the bleeding source (Figure 1). In many cases, direct visualization of the bleeding source and cauterization of injured vessels stops the hemorrhage (Figure 2). Several techniques have been suggested to control bleeding from the internal maxillary artery such as ligation of the external carotid artery and angiographic embolization. Emergency access to vascular embolization is crucial. If a patient has severe bleeding, the surgeon should not waste time and intervene immediately. The collateral arteries and the anastomoses between circulations lead to the limited success of surgical ligation of the external carotid artery [9]. A recent study recommended use of tranexamic acid irrigation in obviating perioperative blood loss during orthognathic surgery [10].
\nPossible bleeding sources during LeFort I osteotomy.
Relationship of osteotomy sites and major hemorrhage sources during LeFort I osteotomy.
The infraorbital nerve may be compressed, retracted or transected inadvertently during subperiosteal dissection.
\nInfraorbital nerve injury may have resulted from incorrect separation during disimpaction.
\nAs are the cases with bilateral sagittal ramus osteotomy, nerve sensitivity may return within 6–12 months [11].
\nThe absence of post‐operatory sensitivity after a LeFort I procedure was documented in a study that applied both objective and subjective tests. The results showed a greater incidence of insensitivity in the region above the upper lip, followed by the lower lip and the chin, as was observed in bimaxillary procedures [12]. Neurosensory alterations are normally immediately perceived in the post‐operatory period. They are the result of traction of the infraorbital nerve and direct trauma to the anterior, medial, and posterior superior alveolar nerves, as well as to the nasopalatine nerve and the descending palatal nerve [13]. A study performed at the University of North Carolina on patients undergoing bilateral Sagittal split ramus osteotomy (SSRO) reported that 98% of the patients presented altered sensitivity of the chin 1 month after the operation; with 81% of these patients still presenting with this alteration 6 months after the operation [14]. It is recommended that the patient be advised of possible neurosensory alterations in pre‐operatory visits, thus reducing the patient\'s post‐operatory anxiety [15]. Many studies confirm the return of neurosensory function up to 1 year after surgery [11].
\nAn osteotomy closer than 5 mm of the apices of the teeth has risk of root injuries[16]. In superior repositioning of the maxilla by more than 6 mm, saving of 5 mm margin is not always possible because of the infraorbital foramen position [4]. After orthognathic surgery, loss of vascularity of the dentition is rare, but initial loss of response to pulpal stimulation is common. Long‐term suppressed response to stimulation can occur, but does not necessarily mean a tooth requires endodontic therapy. Although some teeth may eventually become necrotic and require endodontic treatment, many teeth recover without treatment and return to normal coloration and respond to pulp testing [17]. De Jongh et al. studied electric and thermal pulp testing of 10 patients after LeFort I osteotomy in compared to 10 control patients without osteotomy. Their study showed that 71% of 128 teeth were responsive to electric and thermal pulp stimulation and 93% of 136 teeth in the controls [18].
\nSinusitis after LeFort I osteotomy is uncommon, with a reported incidence of septic complications of 0.5–4.8% [19]. Possible explanations for postoperative maxillary sinusitis following LeFort I osteotomy were pre‐existing sinus disease or non‐viable bone fragments left in the maxillary sinus (Figure 3) [20]. A recent study by Valestar et al. showed LeFort I procedure did not influence already existing physical or mental complaints, and nasal ventilation was not negatively affected. However, evaluation of sino‐nasal pathology should be emphasized in the preoperative work‐up [19]. A recent study by Nocini et al. suggested that LeFort I osteotomies can affect the maxillary sinus. The postoperative radiologic views of the maxillary sinus showed inflammation and rhinosinusitis symptoms after LeFort osteotomies. Larger long‐term studies are warranted to clarify the postoperative outcomes and complications (Figure 4) [21].
\nMaxillary sinusitis after LeFort I osteotomy.
Radiologic findings: postoperative computed tomography scan displaying interruption of the medial walls [
Septal malposition may occur during LeFort osteotomy and cause nasal deviation. A possible reason for a cartilagenous septum deviation after a maxillary osteotomy is dislocation by a partially deflated cuff during extubation. Manual inspection of the nares after extubation is important, yet often forgotten [22]. Nasal ventilation generally improves after orthognathic surgery [19]. The most common reason for postoperative nasal‐septal deviation is compression or displacement from inadequate bone removal of the nasal crest of the maxilla or inadequate trimming of the cartilagenous septum (Figure 5) [9].
\nSevere nasal deviation after LeFort I osteotomy.
Avascular necrosis of the maxilla after LeFort I osteotomy has been reported [23]. Usually, these complications relate to the degree of vascular compromise and occur in less than 1% of cases. Rupture of the descending palatine artery during surgery, postoperative vascular thrombosis, perforation of palatal mucosa when splitting the maxilla into segments, or partial stripping of palatal soft tissues to increase maxillary expansion may impair blood supply to the maxillary segments. Sequelae of compromised vasculature include loss of tooth vitality, development of periodontal defects, tooth loss, or loss of major segments of alveolar bone or the entire maxilla (Figure 6) [24]. The risk is increased in patients with anatomical irregularities, such as craniofacial dysplasia\'s, orofacial clefts, or vascular anomalies [5]. The treatment of avascular necrosis of the maxilla is not easily manageable [25]. Regarding no treatment protocol has been established, aseptic necrosis of the maxilla should be treated by maintenance of optimal hygiene, antibiotic therapy to prevent secondary infection, heparinization, and hyperbaric oxygenation [24]. In such cases, it is evident that there is a serious problem with the tissue perfusion immediately postoperatively and the patient must be taken back to the theatre immediately to reposition the segment; delay only makes it worse [26].
\nInitial aspect of the aseptic maxillary necrosis on the seventh postoperative day [
Unfavorable fractures may consist of pterygoid plate, sphenoid bone, and middle cranial fossa fractures. Lanigan and Guest demonstrated pterygomaxillary dysjunction using a curved osteotome and described high‐level fractures of the pterygoid plates with disruption of the pterygopalatine fossa which could extend to the skull base [27]. Unfavorable pterygoid plate fracture is well studied and documented (Figure 7) [28]. Postoperative CT scans indicated that the prevalence of unfavorable fractures of the pterygomaxillary region may be more than previous expectations. Many of these unfavorable fractures are unobserved as there was no CSF leak because of a local soft tissue seal [29]. Renicke et al. reported the incidence of pterygoid plate fracture was 58% following LeFort I osteotomy using postoperative CT scans [30].
\nPossible lines of bad split during LeFort I osteotomy.
Over‐correction after maxillary superior repositioning.
Several factors are responsible for improper maxillary repositioning such as missing a centric relation‐centric occlusion discrepancy preoperatively; failure to achieve the desired maxillary position during isolated maxillary surgery, failure to seat the condyle because of inadequate removal of posterior bony interference and inaccurate vertical positioning [9]. Improper maxillary positioning may occur in correction of vertical maxillary excess. In a study by the first author, the incidence of under‐correction (25%) was more than over‐correction (7.5%) (Figure 8). Five millimeter was considered as a cutoff point for tooth shows at rest and 15 mm at the maximum smile. When tooth show at rest was more than 5 mm presurgically, 50.5% of clinical predictions did not follow the clinical results, and 75% of clinical predictions revealed the same results when the tooth show was less than 5 mm. When the amount of tooth shown in the maximum smile was more than 15 mm presurgically, 75% of clinical predictions did not follow clinical results, and 25% of the predictions met the same results in the maximum smile was less than. Clinical predictions based on the tooth show at rest and at the maximum smile did not have a reliable correlation with clinical results in maxillary superior repositioning. The risk of errors in predictions raised when the amount of superior repositioning of the maxilla increased. Generally, surgeons had a tendency to under‐correct rather than over‐correct. Also clinical prediction is used as a guideline by many surgeons, and it may be associated with variable clinical results [31].
\nTrigemino‐cardiac reflex (TCR) is characterized by cardiac arrhythmia, ectopic beats, atrioventricular block, bradycardia, syncope, vomiting, and asystole. This life‐threatening condition has been documented during simple zygomatic arch elevations, repositioning of blowout and maxillary fractures, orthognathic surgery, and nasoethmoidal fractures [32]. Besides evaluation of at‐risk patients (e.g., children and patients with a medical history of cardiac disease) and high‐risk surgeries (e.g., strabismus), some authors suggested using ketamine for anesthetic induction to decrease the oculocardiac reflex in children undergoing strabismus surgery [32]. Predisposing factors besides cardiac disease are hypoxia and hypercarbia, and use of opioids and β‐blockers. TCR has been identified with a sudden onset of parasympathetic hypotension, apnea, or gastric hypermotility during stimulation of any of the sensory branches of the trigeminal nerve. In some cases, stopping the surgery has resulted in recovery of a normal rhythm; in other cases, anticholinergic drugs and cardiac massage have been mentioned. It is recommended that the anesthesiology team be informed that they may be prepared for mobilization in case of adverse effects. In every high‐risk case presented in the classification, prophylactic administration of, for example, 0.5 mg atropine IV, right before any surgical manipulation known to be risky for TCR is mandatory [32].
\nPotential ophthalmic complications following LeFort I osteotomy includes decrease in visual acuity, extraocular muscle dysfunction, neuroparalytic keratitis, and lacrimal apparatus problems including epiphora [33]. Visual impairment after LeFort I osteotomy may be due to inappropriate separation of the pterygomaxillary junction and resulting fractures extending to the pterygoid plates, sphenoid bone, orbital floor, optic canal, or the skull base. It may damage the optic nerve or its vascular supply. Hemorrhage from the descending palatine artery or sphenopalatine artery in LeFort I osteotomy may be considered as a reason for systemic hypotension. Hemorrhage from the pterygopalatine fossa may leak the orbital cavity through the inferior orbital fissure and increase intraocular pressure (IOP). Hypotensive anesthesia is useful during a maxillofacial operation for blood loss control and enhancing the visibility in the surgical field. The blood flow to the globes may be changed by elevated IOP or dropped systemic blood pressure. Hypotensive anesthesia may potentially reduce the blood supply to the retina and choroid and may cause embolism of the vessels or infarction of the optic nerve. The effect of hypotensive anesthesia on visual impairment has not been clarified yet [34].
\nNasolacrimal duct obstruction (NLDO) after maxillary orthognathic surgery is rare. The absence of an NLDO after LeFort I osteotomy is reasonable because the distance from the nasal opening of the NLD to the levels of osteotomy should be at least 5 mm. The normal distance between the NLD nasal opening and the nasal floor is 11–17 mm. LeFort I osteotomy should be performed 5 mm above the nasal floor. The distal to the proximal part of the NLD is vulnerable to be obstructed after maxillary osteotomy. Secondary inflammatory changes associated with an indirect injury of the NLD lead to obstruction. So surgeons should be aware of the risk of NLDO after orthognathic surgery (Figures 9–11); this can be managed by dacryocystorhinostomy with high success rate [35].
\nRepresentative dacryocystograms showing obstruction of the nasolacrimal duct in a patient who underwent orthognathic surgery and complained of permanent epiphora [
(A) Bad split occurred on the right side. (B) Fixation of bone fragment was done and replaced.
Complete destruction of condyle in a patient, who had undergone orthognathic surgery, was re‐treated with the aid of temporomandibular joint prostheses. Before surgery (A), 3D image of the mandible showing bilateral absence of condyles (B), and after surgery (C) [
Nonunion of segments in conventional LeFort I osteotomy is rare. In segmental osteotomy the risk of nonunion is higher. A good vascular pedicle and bone grafts are crucial. Additional stability of the maxillary segments after fixation with miniplates was suggested by the use of palatal dressing plates. Use of split with intermaxillary fixation may be useful. Three‐dimensional fixation or immobilization can therefore be gained by using miniplates superiorly on the bony aspect, a dressing plate on the palatal aspect, and a wired‐in final surgical wafer on the occlusal aspect of the dentoalveolar segments [36]. If nonunion occurs the surgical site should be reopened, fibrous tissue removed and proper rigid fixation be used for predictable union of segments.
\nTooth damage in segmental osteotomy is not uncommon. In LeFort I, the risk of damage to the teeth roots increases when the horizontal osteotomy line is 5 mm or less. Close proximity to interdental osteotomy cuts or to screws may cause tooth damage, and pulp necrosis [36]. The pulpal blood flow of teeth adjacent to vertical osteotomies of LeFort I segmental maxillary osteotomies has been reported to be decreased significantly at 4 days after surgeries for lateral incisors, canines, and premolars. However, recovery was seen 56 days after operations. The central incisors and teeth that are distant from the vertical osteotomy have blood flow without significant change [37]. It is advocated that presurgical orthodontic separation of the roots by at least 2 mm at the cementoenamel junction and 4 mm at the apical third be maintained to avoid vascular compromise or damage to the roots adjacent to interdental osteotomies [36].
\nSagittal split osteotomy (SSO) is a conventional technique to correct mandibular excess or retrognathia. Since its introduction by Trauner and Obwegeser, SSO has undergone numerous modifications and improvements [38].
\nIn SSO, the inferior alveolar nerve (IAN) may be injured and cause neurosensory disturbance (NSD) in the lower lip. The NSD caused by damage to the IAN is reportedly 9–84.6% [39, 40]. Even with careful surgery, injury to the IAN appears unpredictable. Multiple factors are considered responsible for the development of NSD after SSO, including fixation methods, patient age and surgical procedures, improper splinting, magnitude of mandibular movement, experience of the surgeon, and timing of the postoperative neurosensory evaluation [40]. Injury to the IAN may happen with direct and indirect intraoperative trauma and results in change of sensibility or altered sensation of the lower lip and/or mental region. It may lead the negative effect on patients’ normal functions such as eating, drinking, speech, and social interaction. NSD may affect patients’ everyday lives and can have social or psychological problems [41]. The position of the canal is important in NSD following SSO because the canal position is impacted by osteotomy design and fixation techniques. Nowadays, technologies and software help to evaluate the canal by using CBCT data. An increased distance between the canal and cortical bone presurgically decreased the incidence of postoperative NSD, and high bone density increased of the risk of postoperative NSD. A short post‐operation assessment comparing monocortical and bicortical fixation in a monkey model, showed that IAN function was better with plate fixation than screw fixation [42].
\nAn unfavorable fracture, called a “bad split” although infrequent in the hands of an experienced operator, occasionally develop and can lead to intraoperative difficulties as well as postoperative relapse [43]. Frequently cited reasons for bad split include incomplete osteotomies, using osteotomes that are too large, attempting to split the segments too rapidly presence of impacted third molars, misdirecting the medial osteotomy upward toward the condyle and placement of the medial osteotomy too far superior to the lingula [44].
\nSynonyms used for bad split include “buccal cortical plate fracture” (proximal segment) and “lingual cortical plate fracture” (distal segment) [45]. A bad split can occur during SSO of the mandible regarding precautions. The incidence of bad split is low (0.7% of all SSOs) and patients sometimes have uneventful healing. A significant decrease in incidence did not report during the 20‐year period, and neither technical progress nor the surgeon\'s experience further decreased the frequency of bad splits [45]. It was reported that older patients experienced more bad splits than younger patients [46]. The length of the medial osteotomy line—short or long—did not alter the prevalence of a bad split. The bone thickness of the ramus may affect the type of fracture pattern on the medial side of the ramus [47]. It is clear that certain mandibular anatomic differences can increase the risk of a bad split during SSO [44]. Use of splitters and separators instead of chisels does not increase the risk of a bad split and is therefore safe with predictable results [48].
\nPostoperative infection was reported in studies of patients undergoing bilateral sagittal ramus osteotomy in a period ranging from 5 days to up to a year after surgery. Infections required antibiotic therapy, and in some cases, the patients underwent surgical drainage. osteomyelitis in bilateral sagittal ramus osteotomy was reported [11]. The rate of infection after SSO is up to 11.3%. Infection after SSO is within normal range for a clean‐contaminated procedure. Rigid fixation of the osteotomy may decrease the need for hardware removal [49].
\nIn the literature, there were no uniform criteria defining bleeding complications. Incidence varied between 0.39 and 38% ranging from slight to a life‐threatening hemorrhage.
\nMinor bleeding in SSOs can usually be easily managed by using local anesthetics containing 1:100,000 adrenalines injected before the operation, electrocautery or compression. Excessive blood loss may due to surgical injury of larger vessels. It was reported that excessive blood loss happen mainly to maxillary surgery and the need for blood transfusion in mandibular operations is rarely necessary [50].
\nCondylar resorption (CR) or condylysis can be defined as progressive change of condylar shape with a reduction in mass. Most patients have a decrease in posterior face height, retrognathism, and progressive anterior open bite with clockwise rotation of the mandible. CR may be defined as osteoarthrosis and can be categorized as primary (idiopathic) and secondary. Current evidence on CR is not clear but seen more in female with mandibular deficiency and high mandibular plane angle after bimaxillary surgery; a change in occlusal plane (counterclockwise rotation) may be associated with condylar resorption after orthognathic surgery [51]. It was hypothesized that condylar remodeling is due to an imbalance between mechanical stress applied to the temporomandibular joints (TMJ) and patient’ adaptive capacities. It mainly occurs in 14 to 50‐years‐old women with pre‐existing TMJ dysfunction, estrogen deficiency, and class II malocclusion with a high mandibular plane angle, a diminished posterior facial height and posteriorly inclined condylar neck. Mandibular advancement superior to 10 mm, counterclockwise rotation of the mandible, and posterior condylar repositioning were associated with an increased risk of CROS. Treatment consists of re‐operation in case of degradation after an inactivity period of at least 6 months [52].
\nThe effect of orthognathic surgeries on temporomandibular dysfunction(TMD) is controversial. Some studies support degrees of improvement of TMD [5, 54]. Patients with preexisting TMJ dysfunction undergoing orthognathic surgery, particularly mandibular advancement, are likely to have significant worsening of the TMJ dysfunction postsurgery. TMJ dysfunction must be closely evaluated, treated if necessary and monitored in the orthognathic surgery patients [55]. Use of lag screws, improper control of the proximal segments, and advancement more than 10 mm increases the risk of post‐orthognathic TMD. Orthognathic surgery should not be used solely for management of TMD; patients having orthognathic treatment for correction of their dentofacial deformities with TMD problem had more improvement in their signs and symptoms than deterioration [56].
\nIt is clear that mandibular set back can affect upper airway patency [57]. The amount of narrowing of the pharyngeal airway is smaller in patients undergoing bimaxillary surgery than in patients undergoing mandibular setback surgery [58]. Bimaxillary orthognathic surgery for correction of Class III malocclusion caused an increase of the total airway volume and improvement of polysomnography parameters [59]. Bimaxillary surgery rather than mandibular setback surgery should be used to correct a class III deformity and reduce the risk of obstructive sleep apnea; in fact, bimaxillary surgery may have less effect on the pharyngeal airway patency than mandibular setback surgery alone [60]. A recent study suggested that BSSO presents less change in the pharyngeal airway space after mandibular setback surgery compared to intraoral vertical ramus osteotomy. Furthermore, bimaxillary surgery is superior to mandibular setback surgery alone for the correction of the prognathic mandible, particularly in patients with factors predisposing them to the development of breathing problems [61].
\nIntraoral vertical ramus osteotomy (IVRO) is another approach for the correction of mandibular prognathism. It is very simple and rapid. The inherent anatomic architecture of the mandible poses little interference on the cut surface of the IVRO osteotomy site during mandibular setback, even in cases of severe asymmetry. In addition, because the segments are not fixed, no stress occurs while the distal segment is positioned with the condylar head during and after the osteotomy procedure. Moreover, IVRO has less chance of nerve damage during the osteotomy procedure than SSRO. In addition to advantages provided during the operation, this procedure has various postoperative advantages. It seems to have curable effects on most patients with preoperative TMD [9].
\nClassification of the shape of the osteotomy line [
During IVRO, inferior alveolar nerve (IAN) damage may occur due to the proximity of the vertical osteotomy to the IAN. Preoperatively, the surgeon should evaluate the lingula on radiographic views. The antilingular eminence on the lateral surface of the ramus should be detected. This small protuberance is located at the posterior one third from the posterior border of the ramus and about 10 mm above the occlusal plane of the lower molars in the vertical aspect, which corresponds to the opposite side of the mandibular foramen. The cut should begin 6–7 mm from the posterior border of the ramus. Kawase‐Koga et al. classified the osteotomy line into three types, namely vertical, C‐shaped, and oblique. The most complications occurred in the vertical type cases, and no complications were found in oblique type cases. Condylar luxation was found mainly in unilateral IVRO cases, and bony interference was found in bilateral IVRO cases. These results suggest that the oblique type of osteotomy line has the advantage of avoiding complications (Figure 12) [62].
\nCondylar sagging at the (left side) after IVRO.
Condylar luxation and bony interference are major complications of IVRO [62]. The most troublesome sequelae are skeletal instability and antero‐inferior condylar displacement (sag), with resultant unpredictability of postoperative mandibular position [63]. Condylar luxation is considered to be related to condylar sag, which occurs with the antero‐inferior postoperative displacement of the proximal segment [62]. When the attachments of the masseter and medial pterygoid muscles to the proximal segment are removed extensively, large condylar sag occurs as a complication of IVRO. Condylar luxation is also related to forward force on the condyle from the lateral pterygoid muscle. Normally, the condyle is located in the anterior and inferior position within the glenoid fossa immediately after IVRO. It is gradually reseated into the original position after surgery with the application of intermaxillary elastics [64]. Several techniques have been reported to avoid condylar luxation and interference of the proximal segment. Suturing the periosteum of the segments around the incision with3–0 Vicryl to prevent sagging against the mandibular fossa has been suggested [64]. Rigid fixation is not recommended in IVRO and increases risk of post‐operation open bite. Elastic therapy after osteotomy effectively decreases open bite due to the muscle tension (Figure 13).
\nThe multimodal perception, integration and mental reconstruction of the physical world provide us, amongst other things, with various modality-specific and modality-unspecific features such as colors, timbres, smells, vibrations, locations, dimensions, materials, and aesthetic impressions, which are or can be related to perceived objects and environments. A fundamental issue is the extent to which such features rely on the different modalities and their cooperation. The present study examined and experimentally dissociated the important modalities of hearing and vision by separately providing and manipulating the respectively perceivable information about the physical world, i.e., auralized and visualized spatial scenes. In everyday life, both the egocentric distance to visible sound sources and the size of a surrounding room are important perceptual features, since they contribute to spatial notion and orientation. They are also relevant about artistic renditions and performance rooms, as they relate, for instance, to the concept of auditory intimacy, an important aspect of the quality of concert halls [1, 2, 3]. Accordingly, both the perceived egocentric distance and the perceived room size were investigated, primarily in the context of artistic renditions.
The interaction between hearing and vision occurs in the perception of various features, pertaining for example to intensity [4], localization [5, 6, 7], motion [8, 9, 10], event time [11, 12], synchrony [13], perceptual phonetics [14], quality rating [15], and room perception [16, 17, 18]. Regarding auditory-visual localization and spatial perception, research has focused mainly on horizontal directional localization to date, followed by distance localization, while room size perception has rarely been investigated. Two superior research objectives may be identified in the literature: One objective is the description of human perceptual performance and its dependence on physical cues. Within this context, distance perception was mainly investigated about its
Experimental stimuli may be real objects (e.g., humans, loudspeakers, mechanical apparatuses) that have diverse physical properties and may bear meaning. Otherwise, the investigation of detailed internal mechanisms using behavioral experiments often calls for neutral objects or energetic events with a maximally reduced number of properties and without meaning (e.g., lights, noise) [5]. Criteria for the selection of one of these stimulus categories are essentially the options of stimulus manipulation (e.g., real objects will hardly allow for conflicting stimuli) and the relation of internal and external validity. The advancement of virtual reality provided experimenters with extended and promising options for manipulating complex, naturalistic stimuli. Since the virtualization of real environments is known to affect various perceptual and cognitive features [20, 21, 22, 23], the impact of virtualization has become another prominent research issue.
The perception of distance and room size in the extrapersonal space depends on particular auditory and visual cues provided by the specific scene. Acoustic distance cues are weighted variably and comprise the sound pressure level and the direct-to-reverberant energy ratio [24, 25, 26], spectral attenuation due to air absorption [27], spectral properties due to temporal and directional patterns of reflections of surrounding surfaces [25], as well as spectral alterations due to both near-field conditions and the listener’s head and torso. Interaural level and time differences also appear to play a role, namely in connection with orientations and motions of the sound source and the listener [28, 29, 30].
In real acoustic environments, perceived egocentric distances are known to be compressed above distances of 2 to 7 m [27, 28, 31, 32, 33], hence they are found to be compressed comparably or even more in virtual acoustic environments [32, 34, 35, 36, 37]. However, a largely accurate estimation in high-absorbent and an overestimation in low-absorbent virtual environments were also reported [18, 38].
Acoustic room size cues comprise the room-acoustic parameters clarity (C80, C50) [39, 40, 41], definition (D50) [41], reverberation time (RT) [39, 42, 43], and likely the characteristics of early reflections [39]. In the medium- and large-sized rooms, the perceived room size was shown to be decreased by a binaural reproduction of the acoustic scene compared to listening in situ [40]. A more recent study found, however, that auralization by dynamic binaural synthesis did not affect the estimation of room size [38].
The estimation of the egocentric distance and the dimensions of visual rooms is based on visual depth cues. Common classifications differentiate between pictorial and non-pictorial, monocular and binocular, as well as visual and oculomotor cues. The cues cover different effective ranges: the personal space (0–2 m), the action space (2–30 m) and/or the vista space (> 30 m) [44]. The non-pictorial depth cues comprise three oculomotor cues:
In real visual environments, distances are normally estimated much more precisely and accurately than in real acoustic environments [47]. Beyond about 3 m distances are increasingly underestimated both under reduced-cue conditions [48] and in virtual visual environments, no matter if head-mounted displays or large screen immersive displays are used [38, 49, 50, 51, 52, 53, 54, 55]. However, also largely accurate estimates in virtual visual environments were reported [18, 56]. While the parallax and the observer-to-screen distance [57], as well as stereoscopy, shadows, and reflections [58] were identified to influence the accuracy of distance estimates in virtual visual environments, the restriction of the field of view [59] and the focal length of the camera lens [60] did not take effect. Room size was observed to be overestimated more in a real visual environment than in the correspondent virtual environment [38], as well as underestimated in other virtual visual environments [18].
Turning to acoustic-visual conditions, the experimental combination of acoustic and visual stimuli can be either congruent or divergent regarding positions or other properties. The widely-used variation of the
Under congruent conditions, as experienced in real life, distance estimation is normally highly accurate. Using virtual sound sources and photographs, the additional availability of visual distance information was demonstrated to improve the linearity of the relationship between the physical and the perceptual distance, and to reduce both the within- and the between-subjects variance of the distance judgments [61]. However, virtual acoustic-visual environments may, like virtual visual environments, be subject to compressed distance perception [32], regardless of the application of verbal estimation or perceptually directed action as a measurement protocol [36, 37]. A perceptual comparison between mixed and virtual reality [62] showed that the virtualization of the visual environment increased “aurally perceived” distance and room size estimates (p. 4). The perceived room width was found to be underestimated under the visual, overestimated under the acoustic, and well-estimated under the acoustic-visual conditions [17]. Findings on the accuracy of room size perception are in the same way inconsistent for acoustic-visual environments, as they are for visual environments (see above) [18, 38].
Experiments applying the conflicting stimulus paradigm are normally both more challenging and more instructive [36]. Such experiments have revealed that the localization of an auditory-visual object is largely determined by its visual position, which becomes particularly obvious when compared to the localization of an auditory object. This phenomenon was investigated relatively early [5], and in the case of a lateral or directional offset in the horizontal plane, it was initially referred to as the
In the case of an egocentric distance offset, the phenomenon was initially termed the
Indeed, it has been demonstrated that both visual and acoustic stimulus displacements cause significant changes in egocentric distance estimates [68], indicating that visual and auditory influences occur at the same time, however, with different weights. Regarding auditory features, Postma and Katz varied both visual viewpoints and auralizations in a virtual theater, while asking experienced participants for ratings upon distance and room acoustic attributes [69]. Few attributes (including auditory distance) were significantly influenced by the visual contrasts, whereas most attributes were by the acoustic. Interestingly, a deeper data analysis allowed partitioning participants into three groups being mainly susceptible to auditory distance, loudness, and none of the features, respectively, when exposed to different visual conditions. Amongst others, the study points to the principle, that acoustic and visual information weigh normally highest on auditory and visual features, respectively.
In the course of the advancement of a probabilistic view, it was evidenced that the weights adapt to the reliabilities of the sensory estimates in a statistically optimal manner [70]. Maximum Likelihood Estimation (MLE) modeling was shown to apply to different multisensory localization tasks [47, 71, 72, 73]. Therefore, acoustic-visual stimuli should generally yield a more precise localization than merely acoustic or visual stimuli [72]. The weights may either be experimentally reduced by adding noise to the stimuli, or in turn, if estimated otherwise, indicate the relative acuity of the stimuli and the reliability of their sensory estimates, respectively. For instance, due to missing or largely reduced interaural level difference and interaural time difference cues, auditory positional information has a lower weight in case of a directional or depth offset in the median plane; in this case, localization is therefore more prone to the influence of visual positional information than in the case of a lateral offset [9, 74]. It was found that acoustic and visual contributions are not symmetric about frontal distance: Using LEDs and noise bursts, a “visual capture” effect and a respective aftereffect in frontal distance perception was observed, with a relatively greater visual bias for visual stimulus components being closer than the acoustic components ([75], p. 4).
Combining MLE with Bayesian causal inference modeling [76] is based on the idea that increasing temporal or spatial divergences between sensory-specific stimuli make the perceiver’s inference of more than one physical event more likely, and that multisensory integration takes place only for stimuli subjectively caused by the same physical event. A recent study demonstrated, however, a higher weight of visual signals in auditory-visual integration of spatial signals than predicted by MLE, which might be due to the participants’ uncertainty about a single physical cause [77]. While the result of the causal inference is normally not directly observable, the perceived spatial congruency is: Using stereoscopic projection and wave field synthesis, André and colleagues presented participants with 3D stimuli (a speaking virtual character) containing acoustic-visual angular errors. As expected, a higher level of ambient noise (SNR = 4 dB A) caused a 1.1° shift of the point of subjective equivalence and a steeper slope (−0.077 instead of −0.062 per degree) of the psychometric function. Results were not statistically significant, arguably due to the still too high SNR [78].
Evaluating different variants of probabilistic models through experiments using a virtual acoustic-visual environment and applying a dual-report paradigm, the Bayesian causal inference model with a probability matching strategy was found to explain the auditory-visual perception of distance best [79]. The authors also calculated the sensory weights for visual and auditory distances and found that in windows around the correspondent physical distance, auditory distances were predominantly influenced by visual, while visual distances were slightly influenced by auditory sensory estimates. Visual-auditory weights ranged from 0 to 1, auditory-visual weights from 0 to 0.2. Another study showed a major influence of the acoustic properties of spatial scenes on the collective egocentric distance perception (probably due to a substantially restricted visual rendering), whereas room size perception predominantly relied on the visual properties. The virtual environment was based on the dynamic binaural synthesis, speech and music signals, stereoscopic still photographs of a dodecahedron loudspeaker in four rooms, and a 61″ stereoscopic full HD monitor with shutter glasses [18].
The cited studies applied different data collection methods (e.g., triangulated blind walking, absolute scales, 2AFC), virtualization concepts (no virtualization, direct rendering, numerical modeling), stimulus content types (e.g., speech, noise; LEDs, visible sound sources), visual moves (photographs, videos), stimulus dimensionalities (2D, 3D), and reproduction formats (e.g., monophonic sound, sound field synthesis; head-mounted displays, large immersive screens). Thus, connecting the results in a systematic manner is challenging. Findings on the influences of concrete physical properties on percepts and their parameters have not achieved consistency.
Following a research strategy from the general to the specific, the present study focuses on the influences of the acoustic and visual environments’ properties in their totality. To this end, whole rooms and source-receiver configurations were experimentally varied. To make this feasible, a collective instead of an individual testing approach was taken, i.e., identical test conditions were allocated not to different repetitions (as necessary for data collection in the context of probabilistic modeling) but to different participants. To emphasize external validity and step towards “naturalistic environments” ([65], p. 805), two prototypic types of content (music, speech), six physically existing rooms, direct 3D renderings, long and meaningful stimuli, and a perceptually validated virtual environment were applied.
Methodologically, the prominent co-presence paradigm entails two restrictions. Firstly, the comparison between the acoustic or visual and the acoustic-visual condition involves two sources of variation: (a) the change between the stimulus’ domains (acoustic vs. visual), and (b) the change between the numbers of stimulus domains (1 vs. 2)—i.e., between two basic modes of perceptual processing. Thus, the co-presence paradigm confounds two factors at the cost of internal validity. Since single-domain (acoustic, visual) stimuli do not require a multimodal trade-off, whereas multi-domain (acoustic-visual) stimuli do, different weights of auditory and visual information depending on the basic mode of perceptual processing are expected [79]. To take account of the sources of variation, two dissociating research questions (RQs) were posed.
As a second restriction, the co-presence paradigm does not cover variations within the multi-domain stimulus mode, though it is prevalent in everyday life. Hence, additional RQs ask for the effects of the
RQ 1: To what extent do the perceptual estimates depend on the stimulus domain (acoustic vs. visual, and thereby of the involved modality) as such?
H10: μA = μV.
RQ 2: To what extent do the perceptual estimates depend on the basic mode of perceptual processing (single vs. multi-domain stimuli)?
H20: 2 · μAV = μA + μV.
RQ 3: To what extent do the perceptual estimates depend on the complex acoustic properties of the multi-domain stimuli?
H30: μA1V• = μA2V• = μA3V• = μA4V• = μA5V• = μA6V•.
RQ 4: To what extent do the perceptual estimates depend on the complex visual properties of the multi-domain stimuli?
H40: μA•V1 = μA•V2 = μA•V3 = μA•V4 = μA•V5 = μA•V6.
RQ 5: To what extent do the perceptual estimates depend on the interaction of the complex acoustic and visual properties of the multi-domain stimuli?
H50: μA
Note that not only distance and room size cues but whole scenes were varied, to infer the effects of the entire physical properties of the performance rooms, and therefore of the sensory modalities as such in the context of these environments. RQs 3–5 were made comparative by asking to which extent acoustic and visual properties, and their interaction, do proportionally account for the estimates. For this purpose, commensurable ranges of the factors had to be ensured (2.3, 2.7).
Dependent variables were the perceived egocentric distance and the perceived room size. Where reasonable, the accuracy of the estimates about the physical distances and sizes was also considered.
Answering RQs 1 to 2 requires the application of the co-presence design paradigm. Auralized, visualized, and auralized-visualized spatial scenes are levels of one factor. Answering RQs 3 to 5 requires the acoustic and visual properties of the scenes to be independent factors rather than just levels of one factor, i.e., the application of the conflicting stimulus paradigm. To allow for the quantification of the proportional influences of acoustic properties, visual properties, and their interaction on the perceptual features, however, certain methodological criteria have to be met, because light and sound cannot be directly compared due to their different physical nature. In particular, not only spatiotemporal congruency but also
These considerations result in the need for preservation of all perceptually relevant physical cues and a direct rendering, which we distinguish from fully numerical or partly numerical (hybrid) simulations. The latter approaches are based on assumptions of the physical validity of parametrized material and geometrical room properties, the imperceptibility of structural resolution limits, and/or the physical validity of the applied models on sound and light propagation, including methods of interpolation. By using the term direct rendering, we indicate that the rendering data corresponding to all supported participants’ movements were acquired in situ, i.e., neither calculated from a numerical 3D model nor spatially interpolated (see 2.5.).
With the objective of a clear description of investigated effects, it is indicated to factually and terminologically differentiate between ontological realms (
In view of both the context of the study (artistic renditions, performance rooms) and the complex variation of the stimuli (2.1), the collection of values of various features was of interest. Accordingly, a differential was used. A superordinate objective of the research project is a comparison of the features regarding their respective dependencies on the presences and properties of the acoustic and visual stimuli. Hence, the questionnaire consisted of 21 perceptual features, subdivided into four sets: auditory features (e.g.,
Since the visual stimuli showed only a part of the frontal hemisphere (see 2.5), the participants had to base their assessment of the invisible rear part of the rooms’ length on the visible frontal length, the room shape, their position in the room, and their experiential knowledge on the shape and size of performance rooms. Hence, before analyzing the calculated room volume/size estimates, dispersion and reliability measures of the unidimensional perceptual features were inspected (Table 1).
Measure | ||||
---|---|---|---|---|
Mean | 45.833 | 22.162 | 14.672 | 10.431 |
Standard error of mean | 0.905 | 0.542 | 0.229 | 0.185 |
Cronbach’s Alpha | 0.926 | 0.889 | 0.867 | 0.850 |
Comparison of descriptives and internal consistencies of the unidimensional perceptual features. Calculations are based on the total sample (music and speech group,
Neither the reliability nor the dispersion of the perceived length is conspicuous, since the values for Cronbach’s Alpha are throughout high, for the perceived length even excellent, and the error-to-mean ratios are consistent across the perceptual features. By calculating the cube root of the product of the three collected features, the one-dimensional feature
Since answering RQs 1 to 2 requires the application of the co-presence paradigm, the factor
Label | KH | RT | KO | JC | KE | GH |
---|---|---|---|---|---|---|
Volume | 1899 | 1903 | 7266 | 8079 | 19539 | 22202 |
Size | 12.383 | 12.392 | 19.369 | 20.066 | 26.934 | 28.106 |
Position of receiver (row no./seat no.) | 6/8–9 | 11/178 | 9/20 | 3/- | -/- | 6/9 |
Distance receiver—central source | 9.97 | 9.90 | 9.46 | 7.19 | 15.84 | 9.84 |
Absorption coefficient | 0.18 | 0.20 | 0.30 | 0.17 | 0.02 | 0.28 |
Reverberation time | 1.29 | 0.80 | 1.31 | 2.81 | 7.92 | 2.29 |
Early Decay Time | 1.31 | 0.72 | 1.17 | 2.67 | 8.20 | 1.99 |
Geometric and material properties of the selected rooms (taken from [85]). The index
The number of trials within a test sequence corresponds to the number of experimental conditions (factor level combinations). There are two options for allocating the trials to the scale items: (a) A long stimulus (ca. 2:00 min, cf. 2.5) is judged by means of the 21 items (2.2); there is just one test sequence. (b) A short stimulus (ca. 6 sec) is judged by means of one feature; the number of test sequences corresponds to the number of features. Option (a) was chosen for the following reasons: (1) In the case of option (b), the comparison of the features, as required by the research project (2.2), would be confounded with the repetition of a stimulus, including greater time intervals, whereas it is not in case of option (a). (2) Short stimuli would run counter to both the context (1.1) and the methodological aim (2.2, 2.3) of the study: artistic renditions are much longer than a few seconds, and—particularly regarding the aesthetic and presence features—responses to very short extracts could not be generalized for entire renditions. (3) To yield valid responses, stimuli must provide enough time and information for judgment formation. Building up an aesthetic impression about very short extracts of an artistic rendition would be hardly possible due to the lack of information about the course of time. Thus, artistically self-contained sections were to be presented at least. Long stimuli provide a greater number and variety of physical events, so that each participant can rely on the individually most helpful cues. (4) In the case of option (a) the decision times vary and are unknown, i.e., within the samples, decision times, as well as causal events and their cues, are pooled. On the one hand, this increases the external validity. On the other hand, it also decreases the internal validity, though, to an acceptable level, since both physical distance and size are constant within each stimulus, and attribution of the estimates to detailed cues or events is not part of the research questions (cf. 1.3).
The required sample size was calculated a priori with the aid of the software package G*POWER 3 [85, 86]. Since the groups of the factor
Hypoacusis; criterion: audiogram, hearing threshold >20 dB HL at either ear at any of seven tested frequency bands (125 to 8000 Hz), uncompensated by hearing aid (0 subjects).
Vision deficits; criterion: self-reported deficits, uncompensated by visual aid (0 subjects).
Red and/or green color blindness; criterion: unpassed Ishihara tests for protanomaly and deuteranomaly (3 subjects).
Loss of stereopsis; criterion: unpassed contour stereopsis test using the shutter glasses of the projection system (4 subjects).
Technical incident; failure of saving response data (6 subjects).
Subjectively untrue responses; criterion: implausible perceptual bias (factor ≥ 5) with reference to visual geometric dimensions (14 subjects, most frequent response: “0 m”).
The resultant valid net sample sizes accounted for
As far as possible in a virtual environment, a maximum ecological validity of the stimuli was sought by selecting dedicated performance rooms, artistic content and professional music and speech performers.
Six performance rooms differing in volume (low, medium, high) and average acoustic absorption coefficient (low: αmean(Sabine) < 0.2; high: αmean(Sabine) ≥ 0.2) were selected. Taking into account good speech intelligibility and an accurate perceptibility of the physical room properties (e.g., the visibility of the ceiling height), optimum receiver positions were defined. Based on geometric measures acquired in situ, models of the interior spaces, including the source-receiver-arrangements, were built using the software
The artistic content comprised a musical work and a text, which were chosen to support the perceptibility of the specific room properties by featuring, e.g., impulsivity and sufficient pauses. Two-minute excerpts of Claude Debussy’s String Quartet in g minor, op. 10, 2nd movement, and of Rainer Maria Rilke’s 1st Duino Elegy were selected. The artistic renditions were audio recorded in the anechoic room of the Technische Universität Berlin.
The performances were presented in the Virtual Concert Hall at Technische Universität Berlin, providing virtual acoustic and visual 3D renditions in rooms. It was particularly designed to meet the methodological requirements (2.1, 2.3), and was completely based on directional binaural room impulse responses (BRIRs) and stereoscopic panoramic images acquired in situ by means of the head and torso simulator
Participant in the Virtual Concert Hall (visual condition: KO).
The used BRIRs contained the fixed HRTFs of
The virtual environment did not provide auditory motion parallax cues by supporting lateral motion interactivity and rendering. This was due to limited in-situ acquisition times in the performance rooms. It would have required measurements at several additional positions of the head and torso simulator, depending on the content-specific minimum audible BRIR grid [101, 102], and thus would have multiplied the expenditure of acquisition time beyond the rooms’ availability. However, auditory motion parallax, describing the change in the angular direction of a distant sound source due to the movement of the listener, is assumed to be a supporting cue in absolute distance estimation [103] and known to be a cue in relative depth estimation [104]. Regarding a distance range within the personal space, it was demonstrated by means of a depth discrimination task, and under exclusion of all other distance cues, that auditory motion parallax is exploited by listeners allowing for the perception of distance differences of unknown acoustic stimuli [104]. The cue was shown to be effective for distances between 0.3 and 1.0 m and to be exploitable for lateral head movements within a range of 46 cm. The participants’ sensitivity was highest during self-induced motion. Even sensitive subjects did not perceive distance differences corresponding to angular displacements below 3.2°. This value is higher than the minimum audible movement angles (MAMAs) found in previous research (see [105] for an overview). Regarding a distance range of 1 to 10 m, Rumukkainen and colleagues determined the self-translation minimum audible angle (ST-MAA) to be 3.3° by means of 2AFC discrimination tasks without an external reference [106]. Taking into account the absence of external references in the present study and applying the ST-MAA to the nearest sound source used (7.19 m), a concertgoer would remain below perceptual threshold within a lateral moving range of ±41.5 cm, which corresponds to 150% of a typical concert seat’s width. Respective lateral movements are normally not observed amongst visitors of classical concerts. Since a relative lateral shift of the listener above the perceptual threshold is a precondition for yielding distance information from the auditory motion parallax cue by triangulation, we do expect neither an appreciable bias nor a deterioration of the accuracy of distance perception introduced by the absence of lateral motion interactivity and rendering.
As a result, the Virtual Concert Hall at Technische Universität Berlin provided almost all relevant auditory cues without major biases (rich-cue condition). Exceptions are the missing supports for (rarely performed and normally small) head orientations around the pitch and roll axes.
The sound pressure level of the virtual rendition was adjusted to the sound pressure level of a live rendition of a string quartet in a real room, which was recorded by the calibrated head and torso simulator. Accounting for the gain of the signal chain and the rooms’ STI measures, the level of the scenes’ average sound pressure level at the blocked ear canal was
The acquisition of the visual rendering data applied a fixed stereo base, which does not necessarily accord with the participants’ individual interpupillary distances (IPDs). Respective differences might potentially bias the individual distance and room size perception. To date, experimentation has shown inconsistent effects of the variation of IPD differences on distance perception (see [46] for a review). Most studies cannot be translated into the present study, since they investigated maximum target distances of 1 m and/or used simple numerically modeled objects/environments. Moreover, results differ regarding the significance, the size and/or the direction of the effects. This is apparently due to different rendering technologies (stereoscopic projection, HMD, CAVE), stages of virtualization (mixed reality, virtual reality), target distances (personal space, action space), simulated objects/environments (simple graphic objects, shapes, persons in hallways), and measurement protocols (triangulated distance estimation, blind walking, visual alignment, verbal estimation) [107, 108, 109, 110, 111, 112, 113]. Few experiments investigated distances roughly similar to those used in the present study (about 7 to 16 m). While Willemsen and colleagues did not observe a significant effect of IPD individualization on distance judgments [114], a large variation of the stereo base (0 to 4 times the IPD) showed significant effects on both distance and size judgments: Greater stereo bases resulted in perceptually closer and smaller objects [115]. However, relevance for the descriptive measures, effect sizes and significances of the present study is given rather by the expected value and distribution of the IPD differences than by their individual values. Anthropometric data of the German resident population, from which the sample was drawn, state median IPDs of 61 mm (male persons) and 60 mm (female persons) within the age range of 18 to 65 years [116]. Since the values do nearly exactly meet the stereo base of the target acquisition (60 mm), a substantial collective perceptual bias is unlikely to occur.
Limitations of the visual rendering pertain to the field of view (161° × 56°), which should at least not affect distance perception [59, 117]; the angular resolution (2.1 arcmin), which might affect distance perception [57]; the fixed single focal plane in stereoscopy providing an invariant accommodation cue, so that the connection between convergence and accommodation is suspended [45]; and an undersized luminance of the projection. Data projectors could not provide the luminance and the contrast of the real scenes, especially in connection with shutter glasses. Thus, the luminances of the scenes were fitted into the projectors’ dynamic range while maintaining compressed relations of the luminances. Scene luminances were calculated from exposure time, aperture, and ISO arithmetic film speed of correctly exposed photographs of a centrally placed and vertically oriented 18% gray card according to the additive system of photographic exposure (APEX). The average loss of the luminance value
Since electronic media transform both the physical stimuli and their perception, the replacement of natural by mediatized stimuli for serious experimental purposes demands the knowledge of the perceptual influences of the applied mediatizing system, as also pointed out by [16, 21]. The rendering technique of the Virtual Concert Hall was shown to provide perceptually plausible auralizations [119]. Specifically, the Virtual Concert Hall at Technische Universität Berlin was subjected to a test of auditory-visual validation by comparing a real scene and the correspondent virtual scene [38]. Amongst others, it yielded nearly equal loudness judgments of the real and the virtual environment, whereas the virtual environment—apparently due to the dark surrounding—was perceived slightly brighter than the respective real environment. The virtualization also generally lowered the perceived source distance and the perceived size of a real room—mainly due to the visual rendering. The mere auditory underestimation of source distance and room size introduced by the virtualization amounted only to 6.6 and 1.9%, respectively. The biases are considered in the discussion section.
Each participant ran through the test procedure individually. The procedure lasted about 3 hours and 10 minutes, and comprised color vision and stereopsis tests, audiometry, a socio-demographic questionnaire, a privacy agreement, the clarification of the questionnaire, the measurement of the individual inter-tragus distance (necessary for the technical adaption to the individuals’ ITDs), cabling, a familiarization sequence, and the actual test runs, inclusive of self-imposed breaks.
Arithmetic means standard deviations (Tables 11 and 12) and standard errors were calculated for all combinations of factor levels. The means were plotted against the combinations. According to the test design (2.3), the co-presence paradigm required 3 × 6 repeated measures analyses of variance (rmANOVA), the conflicting stimulus paradigm 6 × 6 rmANOVA for either level of
Source distance showed significant main and interaction effects of
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
1521.061 | 1.782 | 853.503 | 36.965 | <0.001 | 0.086 | 0.306 | 0.122 | 0.430 | >0.999 | |
Error ( | 2016.285 | 87.325 | 23.090 | |||||||
4610.610 | 3.845 | 1199.166 | 137.464 | <0.001 | 0.260 | 0.593 | 0.296 | 0.737 | >0.999 | |
Error ( | 1643.487 | 188.397 | 8.724 | |||||||
597.939 | 7.113 | 84.059 | 9.593 | <0.001 | 0.034 | 0.187 | 0.052 | 0.164 | >0.999 | |
Error ( | 3054.229 | 348.552 | 8.763 |
Results of the rmANOVA for
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
655.466 | 1.683 | 389.381 | 23.350 | <0.001 | 0.058 | 0.248 | 0.073 | 0.387 | >0.999 | |
Error ( | 1038.621 | 62.284 | 16.676 | |||||||
1712.901 | 3.387 | 505.745 | 41.676 | <0.001 | 0.152 | 0.423 | 0.171 | 0.530 | >0.999 | |
Error ( | 1520.729 | 125.315 | 12.135 | |||||||
639.600 | 5.709 | 112.027 | 10.836 | <0.001 | 0.057 | 0.245 | 0.072 | 0.227 | >0.999 | |
Error ( | 2183.952 | 211.245 | 10.338 |
Results of the rmANOVA for
Means (markers) and standard errors (bars) of
Means (markers) and standard errors (bars) of
Regarding RQ 1, a priori main contrasts indicate that the mean estimates at level
Looking at the accuracy of the estimates, the mean estimates differed from the mean physical source distance by −2.36 m (−22.7%) at level
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
469.724 | 5.000 | 93.945 | 13.143 | <0.001 | 0.017 | 0.133 | 0.023 | 0.211 | >0.999 | |
Error ( | 1751.252 | 131.608 | 13.307 | |||||||
6256.608 | 2.602 | 2404.324 | 105.444 | <0.001 | 0.233 | 0.551 | 0.238 | 0.683 | >0.999 | |
Error ( | 2907.446 | 127.509 | 22.802 | |||||||
134.833 | 13.677 | 9.858 | 1.566 | 0.086 | 0.005 | 0.071 | 0.007 | 0.031 | 0.868 | |
Error ( | 4219.961 | 670.192 | 6.297 |
Results of the rmANOVA for
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
375.912 | 1.667 | 225.526 | 9.314 | 0.001 | 0.023 | 0.153 | 0.028 | 0.201 | 0.951 | |
Error ( | 1493.259 | 61.672 | 24.213 | |||||||
2936.460 | 2.724 | 1077.931 | 48.375 | <0.001 | 0.178 | 0.465 | 0.183 | 0.567 | >0.999 | |
Error ( | 2245.993 | 100.794 | 22.283 | |||||||
31.620 | 12.609 | 2.508 | 0.531 | 0.902 | 0.002 | 0.044 | 0.002 | 0.014 | 0.317 | |
Error ( | 2203.942 | 466.540 | 4.724 |
Results of the rmANOVA for
Figures 4 and 5 show the generally lower mean distance estimates for the speech by trend. The figures also illustrate the ranges of the mean estimates. The average range of mean estimates caused by
Means (markers) and standard errors (bars) of
Means (markers) and standard errors (bars) of
Room size showed significant main and interaction effects of
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
10148.965 | 1.651 | 6145.611 | 70.421 | <0.001 | 0.115 | 0.361 | 0.180 | 0.590 | >0.999 | |
Error ( | 7061.808 | 80.919 | 87.270 | |||||||
28109.442 | 3.650 | 7701.183 | 226.890 | <0.001 | 0.319 | 0.685 | 0.379 | 0.822 | >0.999 | |
Error ( | 6070.632 | 178.851 | 33.942 | |||||||
3733.981 | 7.522 | 496.424 | 21.814 | <0.001 | 0.042 | 0.210 | 0.075 | 0.308 | >0.999 | |
Error ( | 8387.358 | 315.667 | 26.570 |
Results of the rmANOVA for
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
6484.837 | 1.513 | 4285.200 | 42.093 | <0.001 | 0.082 | 0.299 | 0.131 | 0.532 | >0.999 | |
Error ( | 5700.224 | 55.992 | 101.803 | |||||||
26573.103 | 2.994 | 8875.557 | 165.259 | <0.001 | 0.337 | 0.713 | 0.383 | 0.817 | >0.999 | |
Error (R | 5949.496 | 101.789 | 58.449 | |||||||
3000.770 | 6.785 | 442.292 | 19.791 | <0.001 | 0.038 | 0.199 | 0.065 | 0.348 | >0.999 | |
Error ( | 5610.150 | 251.030 | 22.349 |
Results of the rmANOVA for
Means (markers) and standard errors (bars) of
Means (markers) and standard errors (bars) of
Regarding RQ 1, a priori contrasts indicated that the mean estimates at level
As with source distance, the range of the mean room size estimates introduced by the factor
Accuracies were generally low regardless of the level of
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
3275.179 | 2.048 | 1599.570 | 25.911 | <0.001 | 0.024 | 0.156 | 0.031 | 0.346 | >0.999 | |
Error ( | 6193.742 | 100.329 | 61.734 | |||||||
32107.238 | 3.203 | 10025.415 | 110.275 | <0.001 | 0.233 | 0.551 | 0.239 | 0.692 | >0.999 | |
Error ( | 14266.617 | 156.927 | 90.913 | |||||||
375.257 | 12.004 | 31.262 | 1.344 | 0.189 | 0.003 | 0.052 | 0.004 | 0.027 | 0.754 | |
Error ( | 13678.450 | 588.172 | 23.256 |
Results of the rmANOVA for
S. o. V. | 1-β | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
3799.130 | 1.446 | 2626.800 | 11.517 | <0.001 | 0.026 | 0.162 | 0.030 | 0.237 | 0.968 | |
Error ( | 12205.465 | 53.513 | 228.084 | |||||||
23087.978 | 2.228 | 10363.307 | 54.821 | <0.001 | 0.155 | 0.429 | 0.160 | 0.597 | >0.999 | |
Error ( | 15582.628 | 82.431 | 189.039 | |||||||
185.804 | 7.540 | 24.642 | 0.662 | 0.716 | 0.001 | 0.035 | 0.002 | 0.018 | 0.296 | |
Error ( | 10382.097 | 278.982 | 37.214 |
Results of the rmANOVA for
Figures 8 and 9 show the generally lower mean room size estimates for the speech by trend. The figures also illustrate the ranges of the mean estimates. The average range of mean estimates caused by
Means (markers) and standard errors (bars) of
Means (markers) and standard errors (bars) of
Most of the results apply likewise to both egocentric distance and room size estimation. RQ 1 asked for the difference between the modalities as such. Mean estimates across the rooms based only on visual information significantly and considerably exceeded those based only on acoustic information, specifically by about a fourth of the mean physical property in the case of distance and by about a third in the case of size. Hence, H11 can be accepted and might be reformulated directionally (H11: μA < μV) for future experimentation. Regarding egocentric distance estimation, the finding is plausible in principle given the reported compression of distance perception in real acoustic environments [27, 28, 31, 32, 33] and virtual acoustic environments [32, 34, 35, 36]. However, it does not agree with [36], who observed a compressed perception of visual distances between 1.5 and 5.0 m, or with [18], who used nearly the same auralization system in connection with smaller distances (1.93–5.88 m) and a restricted visualization. Though the general finding
Regarding RQ 2, there is evidence that the basic mode of perception (processing of single- vs. multi-domain stimuli) as such alters perceptual estimates of geometric dimensions in virtual rooms. Mean estimates based on acoustic-visual stimuli did not equal the average of the mean estimates based on either only acoustic or only visual stimuli. Rather, mean estimates of source distance under the acoustic-visual condition (with acoustic-visually congruent stimuli) were located at 85% (music) of the range between the mean estimates of the levels
Considering the multi-domain mode of perception and applying the conflicting stimulus paradigm, the distance and size estimates depended significantly on both the acoustic and the visual properties of the stimuli (RQs 3 and 4). Generally, about 89% of the explained variance arose from the entire visual and 10% from the entire acoustic information provided by the virtual environment. For both egocentric distance and room size perception, acoustic information showed a slightly greater proportion of explained variance under the speech than under the music condition.
In accordance with the MLE modeling of auditory-visual integration in principle, the acoustic and visual proportions of the explained variance appear to vary strongly according to the availability and, respectively, the richness of the cues in the particular domains: A preliminary experiment under substantially restricted visualization conditions (reduced field of view, reduced spatial resolution, still photographs instead of moving pictures, no maximal acoustic-visual congruency due to visible loudspeakers as sound sources) and non-restricted auralization conditions (identical auralization system) yielded a reversed order of proportions of the explained variance (cf. 2.7), which amounted to 33% for factor
Against the background of the prevalent term
Since the involved modalities and the mode of perception were constant across all factor levels, it may be assumed that VR-induced biases apply likewise to all factor levels of the conflicting stimulus paradigm and their combinations. Hence, the findings on RQs 3 to 5, i.e., the inferential statistics and the
Within the test design, the presence and properties of the acoustic and visual domains were varied to experimentally dissociate the auditory and the visual modalities. Because this variation was categorical, i.e., comprising the entire
There were some additional results on factors and measures which were not explicitly asked for by the RQs:
Both egocentric distance and room size mean estimates, regardless of whether based on acoustic, visual or acoustic-visual stimuli, were obviously lower for speech than for music (though this was not hypothesized or tested, see 2.7). Hence, there is a reason for hypothesizing an influence of content type. This might be due to differences between music and speech regarding, e.g., the bandwidth and energy distribution of the frequency spectra carrying spatial information, perceptual filtering and processing, receptiveness, and/or experiential geometric situations (non-mediatized speech is normally received from lower distances and within smaller rooms than non-mediatized music).
Both the non-significant interaction effect and the particular mean estimates in the experiment according to the conflicting stimulus paradigm indicated that acoustic-visual (mainly spatial) congruency of the stimulus properties did not lead to minimum, maximum or especially accurate mean estimates. This observation is not apt to constitute a general hypothesis, since congruency might play a greater role by contrast with a greater range of the incongruencies (e.g., further-away sound sources) or a greater number of incongruent properties (e.g., including incongruent content).
Egocentric distance mean estimates were most accurate under the acoustic-visual (music) and visual (speech) condition; the room size mean estimates, which were generally inaccurate, likely due to the lack of the visual rendering of the rooms’ rear part, were most accurate under the acoustic condition. In contrast to previous studies [32, 36], regardless of general under- or overestimations of the geometric properties (
Looking at the conflicting stimulus paradigm, the minimum and maximum mean estimates of both source distance and room size did not consistently correspond to the minimum and maximum physical distances and sizes.
Because mean estimates based on purely acoustic stimuli were generally higher in low-absorbent than in high-absorbent rooms (cf. [18]), the range of mean estimates introduced by the factor
Observations (d) and (e) and differences between the studies regarding domain proportions (4.3) give reason to hypothesize that structural and material properties of rooms influence distance perception. Thus, an additional experimental dissociation of the factors physical source distance, physical room size, and acoustic absorption (all else being equal) might be instructive. Furthermore, more detailed physical factors affecting both the acoustic and the visual domain might be disentangled (primary structures, secondary structures, materials). Because of the trade-off between the requirement of ecological stimulus validity and the costs of stimulus production, it might be worth investigating the moderating effects of certain aspects of virtualization (direct rendering, stereoscopy, visually moving persons). In the future, one major aim of research into the perception of geometric properties might be the connection of the modeling of internal mechanisms and the physical-perceptual modeling.
The influence of the presence as well as of the properties of acoustic and visual information on the perceived egocentric distance and room size was investigated applying both a co-presence and a conflicting stimulus paradigm. Constant music and speech renditions in six different rooms were presented using dynamic binaural synthesis and stereoscopic semi-panoramic video projection. Experimentation corroborated that perceptual mean estimates of geometric dimensions based on only visual information considerably exceeded those based on only acoustic information in general. However, the perceptual mode as such (single- vs. multi-domain stimuli) altered the perceptual estimates of geometric dimensions: Under the acoustic-visual condition with acoustic-visually congruent stimuli, the presence of visual geometric information was generally given more weight than the presence of acoustic information. While the egocentric distance estimation under the acoustic-visual condition did not tend to be compressed for music, it did for speech. When only acoustic stimuli were available, the greater amount of acoustic information provided by low-absorbent rooms appeared to be perceptually exploited to improve the accuracy of room size perception. Within the multi-domain mode of perception involving 30 acoustic-visually incongruent and 6 congruent stimuli, auditory-visual estimation of geometric dimensions in rooms relied about nine-tenths on the variation of visual, about one-tenth on the variation of acoustic properties, and negligibly on the interaction of the variation of the particular properties. Both the auditory and the visual sensory systems contribute to the perception of geometric dimensions in a straightforward manner. The observation of generally lower estimates for speech than for music needs to be corroborated and clarified. Further experimentation dissociating the factors source distance, room size, and acoustic absorption (all else being equal) is needed to clarify their particular influence on auditory-visual distance and room size perception.
According to the funding institution (Deutsche Forschungsgemeinschaft) an ethical approval is not required, since the respective indications do not apply [125]. The study was conducted under the ethical principles of the appropriate national professional society (Deutsche Gesellschaft für Psychologie) [126].
This work was carried out as a part of the project “Audio-visual perception of acoustical environments”, funded by the Deutsche Forschungsgemeinschaft (DFG MA 4343/1-1) within the framework of the research unit SEACEN, coordinated by Technische Universität Berlin and Rheinisch-Westfälische Technische Hochschule Aachen, Germany. We thank the staff of the performance rooms for their friendly cooperation, the Berlin Budapest Quartet (Dea Szücs, Éva Csermák, Itamar Ringel, Ditta Rohmann) and actress Ilka Teichmüller for their performances, Alexander Lindau, Fabian Brinkmann, and Vera Erbes for the in-situ acquisition of the rooms’ acoustic and visual properties, Mina Fallahi for the geometric picture editing, Annika Natus, Alexander Haßkerl, and Shamir Ali-Khan for the 3D video shooting and post-production, and all test participants. Finally, we thank the two anonymous reviewers for critically reading the manuscript and suggesting substantial improvements.
The authors have no conflict of interest to declare.
Measure | off | 1 | 3 | 4 | 5 | 5 | 6 | ||
---|---|---|---|---|---|---|---|---|---|
Mean | Music (n = 50) | off | — | 10.87 | 6.85 | 10.25 | 10.52 | 11.80 | 15.47 |
1 | 7.46 | 10.79 | 7.19 | 10.23 | 10.13 | 10.41 | 14.41 | ||
2 | 7.18 | 10.51 | 7.32 | 10.28 | 11.07 | 10.60 | 13.85 | ||
3 | 8.07 | 9.92 | 7.25 | 9.89 | 10.72 | 10.63 | 13.76 | ||
4 | 6.74 | 10.63 | 7.44 | 9.84 | 10.17 | 10.01 | 13.12 | ||
5 | 5.71 | 9.19 | 7.26 | 9.60 | 9.92 | 9.77 | 13.09 | ||
6 | 12.91 | 11.16 | 8.43 | 11.24 | 11.22 | 11.61 | 15.23 | ||
Speech (n = 38) | off | — | 9.96 | 5.91 | 9.56 | 10.33 | 10.19 | 12.45 | |
1 | 7.10 | 8.88 | 6.11 | 8.82 | 8.87 | 9.37 | 11.52 | ||
2 | 8.07 | 8.53 | 6.46 | 8.98 | 9.04 | 9.09 | 11.39 | ||
3 | 6.67 | 8.62 | 6.00 | 8.69 | 8.72 | 8.67 | 11.26 | ||
4 | 5.90 | 8.28 | 5.67 | 8.31 | 8.38 | 8.70 | 10.68 | ||
5 | 5.30 | 7.67 | 6.03 | 8.12 | 8.30 | 8.03 | 10.62 | ||
6 | 11.07 | 9.72 | 7.07 | 9.72 | 9.92 | 9.94 | 12.23 | ||
STD | Music (n = 50) | off | — | 4.36 | 3.04 | 3.53 | 2.59 | 3.54 | 3.61 |
1 | 3.54 | 3.77 | 2.40 | 3.03 | 3.07 | 3.10 | 3.83 | ||
2 | 4.03 | 3.78 | 2.74 | 3.11 | 3.01 | 2.94 | 3.63 | ||
3 | 4.19 | 3.15 | 2.90 | 2.83 | 3.20 | 3.05 | 3.69 | ||
4 | 3.09 | 4.24 | 2.69 | 2.77 | 3.03 | 2.88 | 4.42 | ||
5 | 2.93 | 3.08 | 2.73 | 3.15 | 3.39 | 3.30 | 4.04 | ||
6 | 4.83 | 4.12 | 3.90 | 3.57 | 3.58 | 4.17 | 3.72 | ||
Speech (n = 38) | off | — | 4.10 | 2.02 | 2.76 | 4.25 | 3.90 | 4.10 | |
1 | 3.52 | 3.15 | 2.28 | 2.74 | 2.67 | 2.95 | 4.44 | ||
2 | 4.17 | 3.01 | 2.55 | 2.81 | 2.50 | 3.02 | 3.95 | ||
3 | 3.04 | 3.46 | 2.12 | 2.73 | 2.36 | 2.44 | 4.48 | ||
4 | 2.75 | 2.81 | 1.93 | 2.63 | 2.57 | 3.08 | 4.54 | ||
5 | 3.34 | 3.21 | 2.55 | 2.38 | 2.91 | 2.67 | 4.83 | ||
6 | 5.82 | 3.70 | 2.73 | 3.01 | 3.37 | 3.60 | 4.03 |
Descriptive statistics of
Measure | off | 1 | 3 | 4 | 5 | 5 | 6 | ||
---|---|---|---|---|---|---|---|---|---|
Mean | Music (n = 50) | off | — | 30.76 | 24.39 | 18.36 | 25.03 | 18.79 | 32.28 |
1 | 16.89 | 29.38 | 22.66 | 19.48 | 22.94 | 19.32 | 30.06 | ||
2 | 18.36 | 28.97 | 24.10 | 19.05 | 23.75 | 19.34 | 30.63 | ||
3 | 14.99 | 29.95 | 22.94 | 18.96 | 22.22 | 18.97 | 29.94 | ||
4 | 12.51 | 28.70 | 22.78 | 18.20 | 22.07 | 18.88 | 28.26 | ||
5 | 10.56 | 27.02 | 22.66 | 17.99 | 22.45 | 18.11 | 28.13 | ||
6 | 31.88 | 31.52 | 26.18 | 21.73 | 25.64 | 23.12 | 33.40 | ||
Speech (n = 38) | off | — | 29.29 | 21.56 | 17.18 | 21.41 | 17.43 | 32.04 | |
1 | 16.19 | 26.51 | 22.53 | 17.71 | 20.37 | 18.69 | 29.28 | ||
2 | 20.75 | 27.78 | 23.43 | 19.07 | 20.69 | 19.34 | 30.03 | ||
3 | 11.53 | 25.70 | 21.71 | 17.15 | 19.36 | 17.39 | 28.98 | ||
4 | 9.85 | 25.07 | 20.89 | 16.29 | 19.54 | 17.00 | 26.69 | ||
5 | 8.42 | 24.60 | 20.91 | 17.04 | 18.94 | 16.96 | 26.69 | ||
6 | 31.93 | 29.47 | 26.04 | 20.85 | 23.25 | 21.30 | 33.11 | ||
STD | Music (n = 50) | off | — | 7.01 | 7.09 | 6.67 | 7.45 | 6.79 | 8.76 |
1 | 6.58 | 8.39 | 6.21 | 5.62 | 7.40 | 7.02 | 9.12 | ||
2 | 7.05 | 8.89 | 7.96 | 6.50 | 7.10 | 6.66 | 8.73 | ||
3 | 6.30 | 8.06 | 7.10 | 6.36 | 7.17 | 5.69 | 8.73 | ||
4 | 6.36 | 7.88 | 7.02 | 5.49 | 6.74 | 6.57 | 9.00 | ||
5 | 4.83 | 9.12 | 7.24 | 5.54 | 7.51 | 6.54 | 8.96 | ||
6 | 8.67 | 7.91 | 7.91 | 8.58 | 8.21 | 8.68 | 9.20 | ||
Speech (n = 38) | off | — | 9.68 | 7.31 | 5.97 | 9.02 | 7.43 | 9.43 | |
1 | 7.28 | 10.02 | 7.79 | 8.06 | 8.25 | 8.15 | 11.07 | ||
2 | 7.56 | 9.79 | 8.60 | 7.53 | 8.09 | 8.02 | 11.42 | ||
3 | 5.94 | 11.32 | 10.34 | 7.93 | 7.68 | 7.59 | 12.80 | ||
4 | 3.48 | 11.35 | 9.37 | 6.92 | 8.40 | 7.91 | 12.47 | ||
5 | 5.89 | 10.99 | 10.12 | 8.07 | 9.18 | 8.03 | 12.94 | ||
6 | 8.39 | 9.36 | 8.82 | 10.39 | 9.82 | 9.66 | 10.71 |
Descriptive statistics of
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\n\nThe Open Access Publishing Fee (OAPF) is payable only after your book chapter, monograph or journal article is accepted for publication.
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