Swarnakar R, Yadav SL. Artificial intelligence and machine learning in motor recovery: A rehabilitation medicine perspective. World J Clin Cases 2023; 11(29): 7258-7260 [PMID: 37946764 DOI: 10.12998/wjcc.v11.i29.7258]
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07777043
Submitted on:
October 16, 2023, 13:39
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Reader Comments:
With the arrival of the digital era, big data technology with artificial intelligence as the core is also gradually applied to the field of sports rehabilitation, which has a wide range of applications in the fields of assisted injury assessment and diagnosis, rehabilitation therapy robot, health management cloud platform and other fields, and can help realize the demand for accurate rehabilitation treatment. In the process of summarizing the current application of AI technology in the field of rehabilitation, it is found that the number of studies related to AI technology in the cultivation of sports rehabilitation talents is relatively small, and the content of the studies is fragmented. We read from World Journal of Clinical Cases that Swarnakar R, Yadav SL et al. studied the status of artificial intelligence and machine learning in motor recovery from the perspective of rehabilitation medicine. Understanding the perspectives of how AI and ML can be utilized for motor recovery in rehabilitation settings, e.g., assessment and diagnosis, predictive modeling, individualized treatment planning, sensor-based motion analysis, virtual reality (VR) and augmented reality (AR), adaptive neurorehabilitation, telerehabilitation, and more. It is known that the integration of AI and ML in motor recovery has the potential to improve rehabilitation outcomes, and these technologies can remotely assess a patient's progress in motor rehabilitation and provide personalized feedback. This proactive approach maximizes the chances of better outcomes by tailoring rehabilitation programs based on real-time predictive insights.
Overall, the article is concise and on topic. However, there is less description of the historical background and prior research on the topic of artificial intelligence and machine learning related to exercise rehabilitation, and there is a lack of corresponding theoretical and practical support. This set leads to the fact that this study is limited to the theoretical level of explanation for the research topic, and it is not possible to compare and contrast different views or findings, while it is in a blank or restricted state in the application of intelligent practice in sports rehabilitation. The emergence of new technologies and methods in the future provides new ideas and creates new opportunities for the theory and practice of exercise rehabilitation. Therefore, there is a need for richer topics, systematic theories, and research methods to study the practical skills of artificial intelligence and machine learning on sports rehabilitation assessment and treatment. In conclusion, intelligent information technology plays a crucial role in the process of sports rehabilitation, and its theory and practice deserve continued attention from the academic community.
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