Letter to the Editor
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Oct 16, 2023; 11(29): 7258-7260
Published online Oct 16, 2023. doi: 10.12998/wjcc.v11.i29.7258
Artificial intelligence and machine learning in motor recovery: A rehabilitation medicine perspective
Raktim Swarnakar, Shiv Lal Yadav
Raktim Swarnakar, Shiv Lal Yadav, Department of Physical Medicine and Rehabilitation, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India
Author contributions: Swarnakar R contributed to the conception and design; Swarnakar R and Yadav SL contributed to the literature search and writing.
Conflict-of-interest statement: The authors have no conflicts of interest to declare.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Raktim Swarnakar, MBBS, MD, Doctor, Department of Physical Medicine and Rehabilitation, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, Delhi, India. raktimswarnakar@hotmail.com
Received: July 29, 2023
Peer-review started: July 29, 2023
First decision: August 16, 2023
Revised: September 1, 2023
Accepted: September 18, 2023
Article in press: September 18, 2023
Published online: October 16, 2023
Processing time: 76 Days and 7.3 Hours
Abstract

Artificial intelligence (AI) and machine learning (ML) are powerful technologies with the potential to revolutionize motor recovery in rehabilitation medicine. This perspective explores how AI and ML are harnessed to assess, diagnose, and design personalized treatment plans for patients with motor impairments. The integration of wearable sensors, virtual reality, augmented reality, and robotic devices allows for precise movement analysis and adaptive neurorehabilitation approaches. Moreover, AI-driven telerehabilitation enables remote monitoring and consultation. Although these applications show promise, healthcare professionals must interpret AI-generated insights and ensure patient safety. While AI and ML are in their early stages, ongoing research will determine their effectiveness in rehabilitation medicine.

Keywords: Artificial intelligence; Motor learning; Rehabilitation; Motor recovery; Machine learning; Physical medicine and rehabilitation

Core Tip: Artificial intelligence (AI) and machine learning (ML) are promising to revolutionize motor recovery in rehabilitation medicine. These technologies enable precise movement analysis, personalized treatment plans, and adaptive neurorehabilitation approaches using wearable sensors, virtual reality, augmented reality, and robotic devices. AI-driven telerehabilitation also facilitates remote monitoring and consultation. However, healthcare professionals must interpret AI-generated insights and prioritize patient safety. Ongoing research will determine the true potential of AI and ML in shaping the future of rehabilitation medicine.