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.
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
Table of Contents
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
AuthorsDeepak Gupta Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India. Dr. Deepak Gupta is an assistant professor at Maharaja Agrasen Institute of Technology, Delhi, India. He is an eminent academician, including roles as lecturer, researcher, consultant, community service, PhD, and post-doctorate supervision. Dr. Gupta focuses on rational and practical learning and has contributed important literature in the fields of Human-Computer Interaction, Intelligent Data Analysis, Nature-Inspired Computing, Machine Learning, and Soft Computing. Dr. Gupta has authored/edited a number of books, including Emerging Trends and Roles of Fog, Edge, and Pervasive Computing in Intelligent IoT-Driven Applications, Wiley; Advanced Machine Intelligence and Signal Processing, Springer; Deep Learning for Medical Applications with Unique Data, Elsevier/Academic Press; Explainable Edge AI: A Futuristic Computing Perspective, Springer; Applications of Big Data in Healthcare, Elsevier/Academic Press; and Data Science for Covid-19, Volumes 1 and 2, Elsevier/Academic Press; among others. Ashish Khanna Sr. Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology (MAIT), New Delhi, India. 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. D. Jude Hemanth Professor, ECE Department, Karunya Institute of Technology and Sciences, Coimbatore, India. Dr. D. Jude Hemanth is currently working as a professor in Department of ECE, Karunya University, Coimbatore, India. He also holds the position of "Visiting Professorï¿½ in Faculty of Electrical Engineering and Information Technology, University of Oradea, Romania. He also serves as the "Research Scientistï¿½ of Computational Intelligence and Information Systems (CI2S) Lab, Argentina; LAPISCO research lab, Brazil; RIADI Lab, Tunisia; Research Centre for Applied Intelligence, University of Craiova, Romania and e-health and telemedicine group, University of Valladolid, Spain.
Dr. Hemanth received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006 and Ph.D. from Karunya University in 2013. He has published 37 edited books with reputed publishers such as Elsevier, Springer and IET. His research areas include Computational Intelligence and Image processing. He has authored more than 200 research papers in reputed SCIE indexed International Journals and Scopus indexed International Conferences. Aditya Khamparia Assistant Professor, Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 8 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 75 research papers along with book chapters including more than 15 papers in SCI indexed Journals with cumulative impact factor of above 50 to his credit. Additionally, he has authored and edited five 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, educational technologies, and computer vision.