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001 9780750351829
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008 230905s2023 enka fob 000 0 eng d
020 _a9780750351829
_qebook
020 _a9780750351812
_qmobi
020 _z9780750351805
_qprint
020 _z9780750351836
_qmyPrint
024 7 _a10.1088/978-0-7503-5182-9
_2doi
035 _a(CaBNVSL)thg00083646
035 _a(OCoLC)1396227987
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aR858
_b.A443 2023eb
060 4 _aW 26.5
_bAF256 2023eb
072 7 _aUYQ
_2bicssc
072 7 _aTEC067000
_2bisacsh
245 0 0 _aAffective computing in healthcare :
_bapplications based on biosignals and artificial intelligence /
_cedited by M. Murugappan.
246 3 0 _aApplications based on biosignals and artificial intelligence.
264 1 _aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :
_bIOP Publishing,
_c[2023]
300 _a1 online resource (various pagings) :
_billustrations (some color).
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
490 1 _a[IOP release $release]
490 1 _aIPEM-IOP series in physics and engineering in medicine and biology
490 1 _aIOP ebooks. [2023 collection]
500 _a"Version: 20230801"--Title page verso.
504 _aIncludes bibliographical references.
505 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.
520 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.
521 _aResearchers and industry professionals in affective computing and biomedical engineering.
530 _aAlso available in print.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
545 _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.
588 0 _aTitle from PDF title page (viewed on September 5, 2023).
650 0 _aMedicine
_xData processing.
_993124
650 0 _aArtificial intelligence
_xMedical applications.
_965209
650 0 _aBiosensors.
_992818
650 0 _aHuman-computer interaction.
_964854
650 0 _aUser-centered system design.
_993717
650 1 2 _aMedical Informatics.
_960693
650 1 2 _aArtificial Intelligence.
_958441
650 1 2 _aBiosensing Techniques.
_996633
650 1 2 _aMedical Informatics Applications.
_962913
650 1 2 _aUser-Centered Design.
_996634
650 7 _aArtificial intelligence.
_2bicssc
_958441
650 7 _aTECHNOLOGY & ENGINEERING / Signals & Signal Processing.
_2bisacsh
_996635
700 1 _aMurugappan, M.,
_eeditor.
_996636
710 2 _aInstitute of Physics (Great Britain),
_epublisher.
_917702
776 0 8 _iPrint version:
_z9780750351805
_z9780750351836
830 0 _aIOP (Series).
_pRelease 23.
830 0 _aIPEM-IOP series in physics and engineering in medicine and biology.
830 0 _aIOP ebooks.
_p2023 collection.
856 4 0 _uhttps://iopscience.iop.org/book/edit/978-0-7503-5182-9
942 _cE-Books
999 _c68394
_d68394