Implications of Artificial Intelligence in Next Generation Physiotherapy

Erscheinungsjahr 2027
ISBN: 978-0-443-45172-0
Verlag: Elsevier Science

Buch, Englisch, 220 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 449 g

Implications of Artificial Intelligence in Next Generation Physiotherapy explores how artificial intelligence is transforming the future of physiotherapy across the entire continuum of rehabilitation. Covering musculoskeletal, neurological, cardiopulmonary, sports, paediatric, geriatric, women's health, and community-based physiotherapy, the book highlights how AI is reshaping clinical practice through intelligent assessment, precision rehabilitation, personalized treatment planning, predictive analytics, remote monitoring, and data-driven clinical decision-making.
The book presents comprehensive coverage of emerging AI technologies, including machine learning, deep learning, computer vision, wearable sensors, robotics, virtual and augmented reality, digital twins, tele-rehabilitation, and intelligent clinical decision support systems. It also discusses workload monitoring, movement analysis, biomechanical assessment, functional outcome prediction, patient engagement, and continuous recovery tracking, supported by current research, real-world applications, and clinical case studies.
Designed for researchers, clinicians, educators, students, and healthcare innovators, this book bridges the gap between cutting-edge artificial intelligence and evidence-based physiotherapy practice. By examining both current applications and future directions, it provides readers with the knowledge required to implement AI-driven innovations that enhance diagnostic accuracy, optimize rehabilitation outcomes, improve healthcare accessibility, and advance patient-centred care in the next generation of physiotherapy.

Autoren/Hrsg.

Kaur, Manpreet

Agarwal, Shagun

Ganie, Shahid Mohammad

Sharma, Anand

Fachgebiete

• Naturwissenschaften Biowissenschaften Humanbiologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Vorklinische Medizin: Grundlagenfächer Physiologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Vorklinische Medizin: Grundlagenfächer Anatomie

Inhaltsverzeichnis

1. Introduction to AI-based Rehabilitation System
2. Different AI-based Therapeutic Innovations
3. Type of AI-based Therapeutic Innovations
4. Machine Learning Based Rehabilitation System
5. AI Powered Rehabilitation Tools
6. AI-based Evaluation and Assessment Methods or Diagnosis Procedures
7. Impact of AI-based Rehabilitation System in Improving Quality of Life
8. Benefits Related to Prospective Applications of AI-based Rehabilitation
9. Patient Preparation and Ethical Concerns Related to AI-based Rehabilitation
10. Challenges in Integrating AI with Rehabilitative Wearable Devices
11. Security and Privacy Issues Regarding AI-based Therapeutic Protocols
12. Protocols for Overcoming AI Challenges
13. Remedies for Overcoming AI Challenges

Über Autor(innen)

Sharma, Anand
Dr. Anand Sharma received his BTech, from IIT, Bhopal. After MTech, He was awarded with PhD. He has been working as an associate professor in the Department of CSE, Mody University of Science and Technology, Lakshmangarh, for the last 14 years. He has more than 16 years of experience in teaching and research. He is an active researcher who has 180 plus publications (inclu-ding patents, journal papers, conference proceedings, book chapters, and books from reputed international publishers).He is serving in an advisory capacity in several international journals as an editorial member and in international conferences as a member of the technical program committee or organizing committee. He is a member of IEEE, IET, and IE (India), and a life member of CSI and ISTE.

Ganie, Shahid Mohammad
Dr. Shahid Mohammad Ganie is an Assistant Professor in the Department of Health Information Management and Technology, College of Applied Medical Sciences, King Faisal University, Al-Ahsa, Saudi Arabia. His research interests include Data Analytics, Explainable Artificial Intelligence, Machine Learning, Deep Learning, Healthcare Informatics, Medical Image Analysis, and Smart Healthcare Systems. He has published over multiple research articles in peer-reviewed journals and international conferences, holds two healthcare-related patents, and has edited several books. His research focuses on developing AI-driven solutions for healthcare applications.

Kaur, Manpreet
Dr. Manpreet Kaur (PT) is a dedicated physiotherapist and Assistant Professor at Chandigarh University, India, specializing in neurological disorders. With a Bachelor’s and Master’s degree in Physiotherapy, she has extensive teaching experience, instructing undergraduate physiotherapy and pharmacy students in anatomy, physiology, and practical applications. Dr. Kaur actively treats patients in outpatient departments while guiding final-year students in their projects and dissertations. She serves as the lab in-charge of the physiotherapy lab and engages in research, contributing to publications and securing patents for innovative rehabilitation devices. Her passion for education and patient care is complemented by her diverse interests, including music, cooking, and sports. Fluent in Hindi, English, and Punjabi, Dr. Kaur aims to enhance the quality of neurorehabilitation education and treatment, making a significant impact on both her students and patients.

Agarwal, Shagun
He has received his BPT degree from Swami Vivekananda national Institute of Rehabilitation and Research Centre in 1999, MPT from Jamia Hamdard University in 2003. He awarded with PhD degree in Amity University. Currently he is working as a dean in Department of Physiotherapy, Galgotias University, Noida (UP), India. He is an active member of IAP association and conducting number of workshops related to physiotherapy practices. He has numerous research papers published in reputed journal.