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.
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