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Wearable Telemedicine Technology for the Healthcare Industry
Product Design and Development
- 1st Edition - November 16, 2021
- Editors: Deepak Gupta, Ashish Khanna, D. Jude Hemanth, Aditya Khamparia
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 8 5 8 5 4 - 0
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 8 5 8 1 0 - 6
Wearable Telemedicine Technology for the Healthcare Industry: Product Design and Development focuses on recent advances and benefits of wearable telemedicine techniques for remot… Read more
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Request a sales quoteWearable 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
Academics (scientists, researchers, MSc. PhD. students) from the fields of Biomedical Engineering, Computer Science, Biology, and Information Technology. The audience also includes researchers and practitioners in Intelligent Systems, Computer Vision, Software Engineers, and Medical Expert Diagnostic systems. Interested professionals in Health Policy, Public Health Management, Data Modeling, and Data Analysis
- Cover Image
- Title Page
- Copyright
- Table of Contents
- Contributors
- Authors bios
- Preface
- Chapter 1 Human body interaction driven wearable technology for vital signal sensing
- Abstract
- 1.1 Introduction
- 1.2 Literature survey
- 1.3 Proposed model
- 1.4 Results and discussion
- 1.5 Conclusion
- References
- Chapter 2 HealthWare telemedicine technology (HWTT) evolution map for healthcare
- Abstract
- 2.1 Introduction
- 2.2 Features and types of health wearable technology
- 2.3 Uses of HWTT in healthcare
- 2.4 Advantages of integrating HWTT into electronic medical records (EMR)
- 2.5 Applications of health ware telemedicine technology
- 2.6 Impact on healthcare and healthcare workers from mHealth wearables
- 2.7 Challenges of integrating HWTT
- 2.8 Future trends in healthcare technology
- 2.9 Conclusion
- References
- Chapter 3 Blockchain: A novel paradigm for secured data transmission in telemedicine
- Abstract
- 3.1 Introduction
- 3.2 Blockchain opportunities in telemedicine
- 3.3 Blockchain-based telehealth systems: challenges and obstacles
- 3.4 Blockchain architectures for clinical data sharing: state-of-the-art
- 3.5 Sample case studies and proposed models
- 3.6 COVID-19 pandemic: latest developments and research
- 3.7 Open research challenges and future scope
- 3.8 Conclusion
- References
- Chapter 4 Wearable technology and artificial intelligence in psychiatric disorders
- Abstract
- 4.1 Introduction to wearable technologies
- 4.2 Introduction to AI
- 4.3 How AI and wearable technology are interlinked
- 4.4 Types of wearable technologies in a psychiatric disorder
- 4.5 AI methods in psychiatric disorders
- 4.6 Applications of wearable technology and AI
- 4.7 How wearable device helps in tracking disorders
- 4.8 Case studies on AI and wearable technologies in a psychiatric disorder
- 4.9 Conclusion
- References
- Chapter 5 Controlling vital signs of patients in emergencies by wearable smart sensors
- Abstract
- 5.1 Introduction
- 5.2 Literature review
- 5.3 Monitoring vital signs in epidemic conditions
- 5.4 Discussion
- 5.5 Conclusion
- References
- Chapter 6 A novel compressive sensing with deep learning–based disease diagnosis model for smart wearable healthcare devices
- Abstract
- 6.1 Introduction
- 6.2 The proposed CSDDS-SW model
- 6.3 Performance evaluation
- 6.4 Conclusion
- References
- Chapter 7 Blockchain-based secure data sharing scheme using image steganography and encryption techniques for telemedicine applications
- Abstract
- 7.1 Introduction
- 7.2 Proposed secure data-sharing scheme
- 7.3 Experimental results analysis
- 7.4 Conclusion
- Conflict of interest
- References
- Chapter 8 Intelligent metaheuristic cluster-based wearable devices for healthcare monitoring in telemedicine systems
- Abstract
- 8.1 Introduction
- 8.2 The proposed MOWWO-SVM model
- 8.3 Results and discussion
- 8.4 Conclusion
- References
- Chapter 9 Class imbalance data handling with deep learning–based ubiquitous healthcare monitoring system using wearable devices
- Abstract
- 9.1 Introduction
- 9.2 Proposed diagnosis model
- 9.3 Experimental validation
- 9.4 Conclusion
- Conflict of interest
- References
- Chapter 10 IoT and wearables for detection of COVID-19 diagnosis using fusion-based feature extraction with multikernel extreme learning machine
- Abstract
- 10.1 Introduction
- 10.2 Related works
- 10.3 The proposed FFE-MKELM model
- 10.4 Experimental validation
- 10.5 Conclusion
- Conflict of interest
- References
- Chapter 11 Internet of things and wearables-enabled Alzheimer detection and classification model using stacked sparse autoencoder
- Abstract
- 11.1 Introduction
- 11.2 Related work
- 11.3 The proposed ADC-SSAE model
- 11.4 Experimental validation
- 11.5 Conclusion
- Conflict of interest
- References
- Index
- No. of pages: 192
- Language: English
- Edition: 1
- Published: November 16, 2021
- Imprint: Academic Press
- Paperback ISBN: 9780323858540
- eBook ISBN: 9780323858106
DG
Deepak Gupta
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.
Affiliations and expertise
Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, IndiaAK
Ashish Khanna
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.
Affiliations and expertise
Sr. Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology (MAIT), New Delhi, IndiaDH
D. Jude Hemanth
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 Professor” in Faculty of Electrical Engineering and Information Technology, University of Oradea, Romania. He also serves as the “Research Scientist” 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.
Affiliations and expertise
Professor, ECE Department, Karunya Institute of Technology and Sciences, Coimbatore, IndiaAK
Aditya Khamparia
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.
Affiliations and expertise
Assistant Professor, Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, IndiaRead Wearable Telemedicine Technology for the Healthcare Industry on ScienceDirect