Mobile Health: Advances in Research and Applications


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Series: Health Care in Transition

BISAC: MED000000

Smart health technologies continue to gain research interest across the globe in this digital era. Researchers are focusing on advancements in healthcare systems to make human life better. Also, such advancements help in early disease diagnosis and prevention of the worst diseases. Designing smart healthcare systems is possible only because of recent developments in artificial intelligence, machine learning and IoT technologies. Though mHealth refers to all mobile devices which can communicate data, mobile phones are presently the most popular platform for mHealth delivery. Ninety-four percent of the world population owns/uses a mobile phone, making mobile phones an optimal delivery platform for mHealth interventions. mHealth may catalyse the healthcare delivery model from a historical/episodic model into a tangible/patient-centric model. mHealth is being viewed progressively by many as an essential technology metaphor to achieve rich, vigorous patient engagement, ultimately achieving a patient-centric paradigm change.

This book will discuss diverse topics to explain the rapidly emerging and evolving mobile health and artificial perspective, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various research domains. It presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of as well as the hindrances to mHealth. The wide variety in topics it presents offers readers multiple perspectives on a variety of disciplines.

The aim of this edited book is to publish the latest research advancements in the convergence of automation technology, artificial intelligence, biomedical engineering and health informatics. This will help readers to grasp the extensive point of view and the essence of recent advances in this field. This book solicits contributions which include theory, case studies and computing paradigms pertaining to healthcare applications. The prospective audience would be researchers, professionals, practitioners, and students from academia and industry who work in this field. We hope the chapters presented will inspire future research from both theoretical and practical viewpoints to spur further advances in the field.

Table of Contents


Chapter 1. Role of IoT in Healthcare: An Overview
(Sachin Kashyap, Brij Bhushan Sharma, Nagesh Kumar, Pankaj Vaidya and Gaurav Gupta – Yogananda School of A.I., Computers and Data Sciences, et al.)

Chapter 2. Wearable Devices: Pros and Cons
(Pankaj Vaidya and Brij Bhushan Sharma – Yogananda School of AI, Computer and Data Sciences, Shoolini University of Biotechnology and Management Sciences, Solan, Himachal Pradesh, India)

Chapter 3. Decision Support Algorithms for Data Analysis
(Ajay Sharma, Sameer, Tarun Pal, Varun Jaiswal – Dept of Biotechnology and Bioinformatics Jaypee University of Information Technology JUIT, et al.)

Chapter 4. Innovation Insight for Healthcare Provider Digital Twins: A Review
(Chitresh Sharma and Gaurav Gupta – Scientific Data Acquisition Competence Centre Leader, L’Oréal Paris, Paris, France, et al.)

Chapter 5. LASIK Innovation Technology for Disease Identification During Lactation
(G. S. Pradeep Ghantasala and Anuradha Reddy – Department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Punjab, India, et al.)

Chapter 6. A Prospective and Comparative Study of Machine and Deep Learning Techniques for Smart Healthcare Applications
(Ahmad Waleed Salehi, Gaurav Gupta and Sonia – Yogananda School of AI Computers and Data Science, Shoolini University, Solan, Himachal Pradesh, India)

Chapter 7. Context-Aware Mobile Healthcare for Smart Health Services in Nursing Homes
(Kalpana Verma – Kasturba Medical College, Mangalore, India)

Chapter 8. Context-Aware Mobile Healthcare for Smart Health Services in Nursing Homes
(Kalpana Verma – Kasturba Medical College, Mangalore, India)

Chapter 9. Machine Learning Techniques to Fight Against Pandemic: A Review
(Bharti Thakur and Nagesh Kumar – Yogananda School of Artificial Intelligence, Computers and Data Science, Bajhol, Himachal Pradesh, India, et al.)

Chapter 10. Computational Approaches for Malaria Diagnosis Using Machine Learning: A Review
(Vandana, Kapil Sethi, and Ankit Gupta – School of Electrical and Computer Science, Shoolini University of Biotechnology and Management Sciences, Solan, Himachal Pradesh, India, et al.)

Chapter 11. Can Mobile Health Technology Improve Health Related Quality of Life of Chronic Disease Patients in Emerging Economies? “Happy Heart” A Randomized Controlled Trial in India
(Yojna Sah Jain, Vaishali M. Patil, Praful Jain and Omar Nada – School of Medical and Allied Sciences, K.R. Mangalam University, Gurugram, Haryana, India, et al.)


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