Mayelana nale ebook
Empower your practice with this definitive resource that bridges the gap between artificial intelligence and biomechanics, providing the essential tools and knowledge to optimize assessments, personalize treatment plans, and predict recovery outcomes in the rapidly evolving landscape of modern physiotherapy.
The integration of artificial intelligence (AI) with biomechanics in physiotherapy represents a transformative shift in the healthcare landscape, driven by rapid technological advancement and an increasing emphasis on personalized, data-driven care. Over the past decade, AI has progressed from theoretical exploration to practical clinical application, enabling enhanced decision-making and improved patient outcomes. This book examines the intersection of artificial intelligence and physiotherapy with a focused emphasis on biomechanics, exploring how AI can optimize biomechanical assessments, support individualized treatment planning, and predict patient progress in clinical settings. As demand grows for AI-driven innovation in rehabilitation, this volume serves as an essential resource for physiotherapists, clinicians, and researchers seeking to understand and adopt these emerging technologies to advance practice and improve rehabilitation outcomes.
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Mayelana nomlobi
Abhishek Kumar, PhD is an Assistant Director and Professor in the Computer Science and Engineering Department at Chandigarh University, Punjab, India. With over 13 years of teaching experience, he has published more than 170 peer-reviewed papers and successfully supervised four Ph.D. scholars, with four more currently under his guidance, along with more than 30 M. Tech projects. He holds a Ph.D. from the University of Madras and completed postdoctoral research at Universidad de Castilla-La Mancha, Spain. His research interests span artificial intelligence, renewable energy systems, image processing, and data mining. An award-winning researcher, Dr. Kumar has received several accolades, including the Sir C.V. Raman National Award (2018), and holds a patent. An accomplished author and editor, he has authored seven books and edited 51 volumes with reputed publishers.
T. Ananth Kumar, PhD is an Associate Professor and Head of Computer Science and Engineering at IFET College of Engineering, India. He has edited six books, published numerous book chapters and patents, and presented research at national and international conferences. His research interests include networks on chips, computer architecture, and application-specific integrated circuit design. He has edited and authored 12 books and has written many book chapters.
Sachin Ahuja, PhD is a Professor and Executive Director of UIE at Chandigarh University. He has led multiple funded research projects in artificial intelligence, machine learning, and data mining and has contributed to numerous academic books. He has also served as a guest editor for special issues in reputed international journals.
J.P. Ananth, PhD is a Professor and Director of the Internal Quality Assurance Cell, Dayananda Sagar University, Bangalore. His research has been published widely in peer-reviewed journals, and he serves as a reviewer for several international journals and conferences. His research interests include computer vision, pattern recognition, artificial intelligence, and data analytics.
S. Oswalt Manoj, PhD is a committed academician and researcher, currently serving as a Professor in the Department of Computer Science and Engineering at Alliance University, Bengaluru. With rich experience in teaching, research, mentoring, and academic leadership, he has guided several Ph.D. scholars and contributed extensively to doctoral committees under Anna University, Chennai. He holds a Ph.D. in Information and Communication Engineering from Anna University, Chennai, with his research focused on Deep Learning-based Rainfall Prediction for Agricultural Applications. He also holds undergraduate and postgraduate degrees in Computer Science and Engineering from Anna University and its affiliated institutions. His areas of academic interest include Machine Learning, Deep Learning, Big Data Analytics, Cloud Computing, and Quantum Computing.
