06158nam a2200709 i 45000010014000000030004000140050017000180060019000350070015000540080041000690200025001100200024001350200025001590200027001840240035002110350025002460350022002710400040002930500023003330600025003560720016003810720023003972450130004202460066005502640098006163000071007143360021007853370026008063380032008324900027008644900071008914900034009625000043009965040041010395051748010805200986028285210094038145300029039085380036039375380078039735450594040515880061046456500031047066500051047376500016047886500032048046500033048366500025048696500029048946500027049236500038049506500026049886500037050146500069050517000029051207100054051497760049052038300031052528300072052838300034053558560059053899780750351829IOP20251030124216.0m    eo  d        cr cn |||m|||a230905s2023    enka   fob    000 0 eng d  a9780750351829qebook  a9780750351812qmobi  z9780750351805qprint  z9780750351836qmyPrint7 a10.1088/978-0-7503-5182-92doi  a(CaBNVSL)thg00083646  a(OCoLC)1396227987  aCaBNVSLbengerdacCaBNVSLdCaBNVSL 4aR858b.A443 2023eb 4aW 26.5bAF256 2023eb 7aUYQ2bicssc 7aTEC0670002bisacsh00aAffective computing in healthcare :bapplications based on biosignals and artificial intelligence /cedited by M. Murugappan.30aApplications based on biosignals and artificial intelligence. 1aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :bIOP Publishing,c[2023]  a1 online resource (various pagings) :billustrations (some color).  atext2rdacontent  aelectronic2isbdmedia  aonline resource2rdacarrier1 a[IOP release $release]1 aIPEM-IOP series in physics and engineering in medicine and biology1 aIOP ebooks. [2023 collection]  a"Version: 20230801"--Title page verso.  aIncludes bibliographical references.0 a1. Anxiety recognition using a new EEG signal analysis approach based on sample density in a Chebyshev chaotic map / Faezeh Daneshmand-Bahman and Ateke Goshvarpour -- 2. Evaluating cognitive load during lexical decision tasks for monolinguals and bilinguals using EEG / Mahesh Veezhinathan, B. Geethanjali, Sukeerthi Sakthivel and RaamaNarayanan AnanthaNarayanan -- 3. Detection of psychological stress using principal component analysis of phonocardiography signals / Amandeep Cheema and Mandeep Singh -- 4. Affective computational advertising based on perceptual metrics / Soujanya Narayana, Shweta Jain, Harish Katti, Roland Goecke and Ramanathan Subramanian -- 5. Machine-learning-based emotion recognition in arousal-valence space using photoplethysmogram signals / Md. Nazmul Islam Shuzan, Moajjem Hossain Chowdhury, Md. Shafayet Hossain, Md. Sakib Abrar Hossain and Muhammad E.H. Chowdhury -- 6. EEG-based human emotion classification from channel-wise feature extraction and feature selection / Lucky Odirile Mohutsiwa and Rodrigo S. Jamisola Jr. -- 7. Detection of physiological body movements in affective disorder patients using EEG signals and deep neural networks / Jason Elroy Martis, M.S. Sannidhan, Sunil Kumar Aithal, R. Balasubramani and K.B. Sudeepa -- 8. Voice-enabled real-time affective framework for negative emotion monitoring / Parker Wilmoth and Prabha Sundaravadivel -- 9. Differential diagnosis tool in healthcare application using respiratory sounds and convolutional neural network / Rajkumar Palaniappan, Kenneth Sundaraj, Fizza Ghulam Nabi and Vikneswaran Vijean -- 10. Virtual reality and augmented reality based affective computing applications in healthcare, challenges, and its future direction / Suma Dawn.3 aHealthcare is one of the most promising applications of affective computing, where advances using biomedical signals have grown rapidly. This comprehensive book begins with an introduction to affective computing and affective computing models, artificial intelligence, probability theory, and statistical learning. It discusses topics such as noise elimination and baseline wandering effects of biomedical signals, and then proceeds to review biomedical signal acquisition and pre-processing. In this book, biomedical signals in affective states are discussed as well as artificial intelligence techniques used to classify biomedical signals, such as artificial neural networks and support vector machines. A discussion of affective computing applications in neurodegenerative diseases and neurological disorders concludes the book. Recent research is discussed alongside future challenges in these areas. Part of IPEM-IOP Series in Physics and Engineering in Medicine and Biology.  aResearchers and industry professionals in affective computing and biomedical engineering.  aAlso available in print.  aMode of access: World Wide Web.  aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.  aProfessor Dr. M. Murugappan has worked at Kuwait College of Science and Technology (KCST), Kuwait, as a Full Professor in Electronics in the Department of Electronics and Communication Engineering since 2016. He has received more than 750K in research grants from Malaysia, Kuwait, and the UK. His publications include more than 140 peer-reviewed conference proceedings papers, journal articles, and book chapters. He is interested in affective computing, the Internet of Things (IoT), brain-computer interface, neuromarketing, signal/medical image processing, and artificial intelligence.0 aTitle from PDF title page (viewed on September 5, 2023). 0aMedicinexData processing. 0aArtificial intelligencexMedical applications. 0aBiosensors. 0aHuman-computer interaction. 0aUser-centered system design.12aMedical Informatics.12aArtificial Intelligence.12aBiosensing Techniques.12aMedical Informatics Applications.12aUser-Centered Design. 7aArtificial intelligence.2bicssc 7aTECHNOLOGY & ENGINEERING / Signals & Signal Processing.2bisacsh1 aMurugappan, M.,eeditor.2 aInstitute of Physics (Great Britain),epublisher.08iPrint version:z9780750351805z9780750351836 0aIOP (Series).pRelease 23. 0aIPEM-IOP series in physics and engineering in medicine and biology. 0aIOP ebooks.p2023 collection.40uhttps://iopscience.iop.org/book/edit/978-0-7503-5182-9