Wearable Telemedicine Technology for the Healthcare Industry (eBook)

Product Design and Development
Artikelnummer: 978-0-323-85810-6
Einband: Adobe Digital Editions
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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Wearable Telemedicine Technology for the Healthcare Industry: Product Design and Development focuses on recent advances and benefits of wearable telemedicine techniques for remote health monitoring and prevention of chronic conditions, providing real time feedback and help with rehabilitation and biomedical applications. Readers will learn about various techniques used by software engineers, computer scientists and biomedical engineers to apply intelligent systems, artificial intelligence, machine learning, virtual reality and augmented reality to gather, transmit, analyze and deliver real-time clinical and biological data to clinicians, patients and researchers. Wearable telemedicine technology is currently establishing its place with large-scale impact in many healthcare sectors because information about patient health conditions can be gathered anytime and anywhere outside of traditional clinical settings, hence saving time, money and even lives. - Provides readers with methods and applications for wearable devices for ubiquitous health and activity monitoring, wearable biosensors, wearable app development and management using machine learning techniques, and more - Integrates coverage of a number of key wearable technologies, such as ubiquitous textile systems for movement disorders, remote surgery using telemedicine, intelligent computing algorithms for smart wearable healthcare devices, blockchain, and more - Provides readers with in-depth coverage of wearable product design and development

Wearable Telemedicine Technology for the Healthcare Industry: Product Design and Development focuses on recent advances and benefits of wearable telemedicine techniques for remote health monitoring and prevention of chronic conditions, providing real time feedback and help with rehabilitation and biomedical applications. Readers will learn about various techniques used by software engineers, computer scientists and biomedical engineers to apply intelligent systems, artificial intelligence, machine learning, virtual reality and augmented reality to gather, transmit, analyze and deliver real-time clinical and biological data to clinicians, patients and researchers. Wearable telemedicine technology is currently establishing its place with large-scale impact in many healthcare sectors because information about patient health conditions can be gathered anytime and anywhere outside of traditional clinical settings, hence saving time, money and even lives. - Provides readers with methods and applications for wearable devices for ubiquitous health and activity monitoring, wearable biosensors, wearable app development and management using machine learning techniques, and more - Integrates coverage of a number of key wearable technologies, such as ubiquitous textile systems for movement disorders, remote surgery using telemedicine, intelligent computing algorithms for smart wearable healthcare devices, blockchain, and more - Provides readers with in-depth coverage of wearable product design and development

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VerlagElsevier Science & Techn.
EinbandAdobe Digital Editions
Erscheinungsjahr2021
Seitenangabe192 S.
AusgabekennzeichenEnglisch
Masse26'481 KB
PlattformEPUB
AutorGupta, Deepak (Hrsg.) / Khanna, Ashish (Hrsg.) / Hemanth B. E., M. E. (Hrsg.) / Khamparia, Aditya (Hrsg.)

Über den Autor Deepak (Hrsg.) Gupta

Dr. Deepak Gupta is Assistant Professor in the Department of Computer Science and Engineering of Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India. Previously he has worked in the Department of Computer Science and Engineering of National Institute of Technology Arunachal Pradesh. He received a Ph.D. degree in computer science and engineering from the Jawaharlal Nehru University, New Delhi, India. His research interests include support vector machines, ELM, RVFL, KRR, biomedical applications, and other machine learning techniques. He has published over 80 referred journal and conference papers of international repute. His publications have more than 2382 citations with an h-index of 28 and i10-index of 63 (Google Scholar, 01/02/2025). Recently, he has listed in the world's top 2% of scientists in a study carried out by Stanford University, USA, 2023, 2024. He is Associate Editor of the Journal of Neural Networks, Computers and Electrical Engineering, etc. Prof. Mayank Pandey stands out as Distinguished Academic and Highly Esteemed Professor at Motilal Nehru National Institute of Technology (MNNIT), Allahabad. Renowned for his profound expertise in computer science, he has made significant contributions to research, innovation, and education, inspiring generations of students and peers. He earned his bachelor's degree in computer science engineering from GB Pant Engineering College, Pauri, Garhwal, followed by an M.Tech. from the prestigious Indian Institute of Technology (IIT) Kharagpur, and a doctorate from MNNIT Allahabad. Throughout his illustrious career, Prof. Pandey has exemplified a relentless commitment to advancing knowledge and fostering excellence in teaching, research, and innovation. One of his most notable achievements is his groundbreaking research on video analytics-based crowd management during the Kumbh Mela 2019 in Prayagraj. Dr. Abhinav Kumar works as Assistant Professor in the Department of Computer Science and Engineering at Motilal Nehru National Institute of Technology Allahabad (MNNIT Allahabad), India. Prior to joining MNNIT Allahabad, he worked as Assistant Professor at the Indian Institute of Information Technology Surat (IIIT Surat), Gujarat, India, and Siksha O Anusandhan, Bhubaneswar, Odisha, India. He has obtained a Ph.D. degree in computer science and engineering from the Department of Computer Science and Engineering of the National Institute of Technology Patna, India. His research interests include machine learning, deep learning, crisis informatics, natural language processing, and social networks. Prof. Ponnuthurai Nagaratnam Suganthan currently serves a Professor at the Department of Computer Science and Engineering, Qatar University, having joined in 2022 after a long-standing tenure as Associate Professor at Nanyang Technological University (NTU), Singapore. Originally from Tellippalai, Jaffna, Sri Lanka, he excelled academically at Union College, earning a full scholarship and later completing his B.A., postgraduate certificate, and M.A. in electrical and information engineering at the University of Cambridge during the early 1990s. He received his Ph.D. from NTU in 1995 before embarking on research roles at the University of Sydney (1995-96) and the University of Queensland (1996-99), leading to his long-standing faculty position at NTU. Prof. Suganthan is IEEE Fellow (2015), recognized for his significant contributions to optimization through evolutionary and swarm algorithms, and has consistently been ranked among Thomson Reuters Highly Cited Researchers in Computer Science from 2015 to 2022.

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