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Predictive Algorithms for Rehabilitation and Assistive Systems

Predictive Algorithms for Rehabilitation and Assistive Systems


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About the Book

Advances in predictive algorithms have been integrated into the development and optimization of rehabilitation and assistive technologies. When applied, predictive algorithms, as well as machine learning (ML) models and data analytics, have the potential to create personalized rehabilitation programs and devices. They are important for enhancing the rehabilitation process and improving patient outcomes. As a result, predictive analytics are crucial to advancing healthcare solutions and the field of biomedical engineering. Predictive Algorithms for Rehabilitation and Assistive Systems provides valuable insights into how data-driven approaches can enhance the efficacy of rehabilitation processes, improve patient outcomes, and foster innovation in assistive technology development. Covering topics such as response patterns, maladaptive pain perception, and disease prediction, this book is an excellent resource for biomedical engineers, medical practitioners, policymakers, professionals, researchers, scholars, academicians, and more.

About the Author :
Rajesh Kumar K V is a distinguished academic and researcher currently serving as Chief Technological Scientist at the AI Research Centre and Associate Professor at the School of Business - Business Analytics department, Woxsen University, Hyderabad, India. Currently, he is leading an engineering team working on interdisciplinary research projects. He holds the prestigious Chair Professor of France Belanger of Information Systems and is actively involved as Co-Chairperson of the Centre of Excellence – Sports Analytics and Management. Furthermore, he is the Advertflair Chair Professor in Marketing and Advertising, specializing in AI Projects. His academic credentials include an M. Tech in Embedded Systems and a Ph.D. in Applied Artificial Intelligence in biomechanical engineering. His research specialization is Human Computer Interface-based signal Data Analytics for Bio-Medical Applications, Machine and Deep Learning, and Business Analytics. In 2022, he showcased his expertise in sports analytics at the Data Con LA+ IM Data 2022 conference in the US, California. His significant research contributions were recognized at ICRA 2023-UK in a workshop on Computer Vision for Wearable Robotics by Harvard University. He recently attended as a panel member to discuss “Digital landscape – Beyond AI” at the Digital Innovation Summit – Bucharest, Romania, and “How AI is changing the landscape of work” at the AI Tech Summit in April 2024, in Malaga, Spain. Recently he participated as a panel member to discuss “Future Cars: How Does it Looks Like” at the MOVE Conference, in June 2024 in London, UK. Padmini Ranasinghe , MD MPH is an Assistant Professor at Johns Hopkins School of Medicine. After completing her medical education in Colombo Medical Faculty in Sri Lanka, she completed a residency in combined Internal Medicine and Preventive Medicine along with an MPH at Yale School of Public Health. She is a fellow of ACP, ACPM, and SHM. She is a clinician, educator, and researcher. Currently serving as co-director of education in the Division of Hospital Medicine. She teachers and mentors’ medical students, residents, and public health students. Her research interests are in the health and wellness of medical students, residents, and practicing physicians, disaster medicine, climates and health, global health, chronic disease prevention, health informatics/role of AI in health care, and advocacy & policy. At national level, she has been active in American Medical Association (AMA) and has served as chair of the AMA International Medical Graduate Section for 2013-14. She has been elected to serve on the Council on Science and Public Health (CSAPH) and is currently a member of its executive committee. The mission of the council is to represent the AMA's core belief that scientific evidence is the basis for improving the quality of patient care, promoting medical progress, and enhancing the health of the public. At the state level, she has been elected as the president-elect to MedChi, Maryland State Medical Society to represent physicians of Maryland. Dorianne Feldman is an assistant professor of physical medicine and rehabilitation at the Johns Hopkins University School of Medicine. She focuses on critical care physical medicine and rehabilitation. She combines both her skills as a physical therapist and physiatrist when treating her patients. Dr. Feldman holds B.S. and M.S.P.T. degrees from Boston University, and received her M.D. from the George Washington University School of Medicine. Following medical school, she completed a preliminary year in internal medicine at Mercy Medical Center/University of Maryland and then a residency in physical medicine and rehabilitation at the Johns Hopkins University School of Medicine. She served as chief resident from 2008-2009 for the Department of Physical Medicine and Rehabilitation, and was subsequently appointed as a clinical associate. Dr. Feldman has published extensively, including five chapters in professional books. She has received numerous awards and honors, and was twice the recipient of the Hopkins Healer Award for excellence in patient care during residency. In April 2017, Dr. Feldman was inducted into the Miller-Coulson Academy of Clinical Excellence. Inductees are honored for their professionalism, communication skills, diagnostic prowess, depth of knowledge, ability to negotiate the health care system, passion for patient care and service as a role model to medical trainees.


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Product Details
  • ISBN-13: 9798337301952
  • Publisher: IGI Global
  • Publisher Imprint: Medical Information Science Reference
  • Height: 254 mm
  • No of Pages: 582
  • ISBN-10: 8337301953
  • Publisher Date: 21 May 2025
  • Binding: Paperback
  • Language: English
  • Width: 178 mm


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