Gupta / Khanna / Khamparia | Wearable Telemedicine Technology for the Healthcare Industry | Buch | 978-0-323-85854-0 | sack.de

Buch, Englisch, 192 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 410 g

Gupta / Khanna / Khamparia

Wearable Telemedicine Technology for the Healthcare Industry

Product Design and Development

Buch, Englisch, 192 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 410 g

ISBN: 978-0-323-85854-0
Verlag: William Andrew Publishing


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.
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Weitere Infos & Material


1. Human Body Interaction Driven Wearable Technology for Vital Signal Sensing 2. HealthWare Telemedicine Technology (HWTT) Evolution Map for Healthcare 3. Blockchain: A Novel Paradigm for Secured Data Conduct in Telemedicine 4. Wearable Technology and Artificial Intelligence in Psychiatric Disorders 5. Applying wearable smart sensors for vital signs controlling of patients in epidemics 6. A Novel Compressive Sensing with Deep Learning based Disease Diagnosis Model for Smart Wearable Healthcare Devices 7. Blockchain based Secure Data Sharing Scheme using Image Steganography and Encryption Techniques for Telemedicine Applications 8. Intelligent Metaheuristic Cluster based Wearable Devices for Healthcare Monitoring in Telemedicine Systems 9. Class Imbalance Data Handling with Deep Learning based Ubiquitous Healthcare Monitoring System using Wearable Devices 10. IoT and Wearables for Detection of COVID-19 Diagnosis using Fusion based Feature Extraction with Multi-Kernel Extreme Learning Machine 11. Internet of Things and Wearables Enabled Alzheimer detection and Classification Model using Stacked Sparse Autoencoder


Khanna, Ashish
Dr. Ashish Khanna has 16 years of expertise in teaching, entrepreneurship, and research and development. He received his PhD from the National Institute of Technology, Kurukshetra, India, and completed a post-doc degree at the National Institute of Telecommunications (Inatel), Brazil. He has published around 40 SCI-indexed papers in 'IEEE Transactions', and in other reputed journals by Springer, Elsevier, and Wiley, with a cumulative impact factor of above 100. He has published around 90 research articles in top SCI/Scopus journals, conferences, and book chapters. He is co-author or editor of numerous books, including 'Advanced Computational Techniques for Virtual Reality in Healthcare' (Springer), 'Intelligent Data Analysis: From Data Gathering to Data Comprehension' (Wiley), and 'Hybrid Computational Intelligence: Challenges and Applications' (Elsevier). His research interests include distributed systems, MANET, FANET, VANET, Internet of Things, and machine learning. He is one of the founders of Bhavya Publications and the Universal Innovator Lab, which is actively involved in research, innovation, conferences, start-up funding events, and workshops. He is currently working at the Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, India, and is also a Visiting Professor at the University of Valladolid, Spain.

Khamparia, Aditya
Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision.

Gupta, Deepak
Deepak Gupta is an eminent academician; plays versatile roles and responsibilities juggling between lectures, research, publications, consultancy, community service, PhD and post-doctorate supervision etc. He is working as Assistant Professor at Maharaja Agrasen Institute of Technology (GGSIPU), Delhi,

India. He has served as Editor-in-Chief, Guest Editor, Associate Editor in SCI and

various other reputed journals (IEEE, Elsevier, Springer, Wiley & MDPI). He has

actively been an organizing end of various reputed international conferences. He is

not only backed with a strong profile but his innovative ideas, research's end-results

and notion of implementation of technology in the medical field is by and large

contributing to the society significantly. He has authored/Edited 70 books, and

published 330 scientific research publications in reputed International Journals and

Conferences including 213 SCI Indexed Journals. He has also granted/published 8

patents. He has got a grant of Rs 1.31 CR from Department of Science and

Technology against the Indo-Russian Joint call.


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