AI-DRIVEN REHABILITATION MONITORING SYSTEM FOR REAL TIME EVALUATION OF POST-STROKE PHYSIOTHERAPY OUTCOMES

Authors

  • Kumbala Pradeep Reddy, S Jagadeesh B. Narendra Kumar Author

DOI:

https://doi.org/10.48047/6c574f80

Keywords:

Stroke Rehabilitation, Physiotherapy Monitoring, Artificial Intelligence, Wearable Sensors, Explainable AI, Healthcare Analytics

Abstract

Stroke remains one of the leading causes of long-term physical disability worldwide, often requiring prolonged physiotherapy to restore motor function and improve quality of life. Conventional rehabilitation assessment methods primarily depend on periodic clinical observations and therapist evaluations, which may not capture continuous  changes in patient performance during therapy sessions

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References

W. H. O. Stroke Factsheet, “Global health estimates for stroke-related disability and mortality,” World Health Organization, Geneva, Switzerland, 2022.

B. H. Dobkin, Rehabilitation After Stroke, 2nd ed. New York, NY, USA: Oxford University Press, 2014.

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Published

2024-08-20

Issue

Vol. 53 No. 03 (2024): Year 2024, Volume 53, Issue 3

Section

Original

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How to Cite

AI-DRIVEN REHABILITATION MONITORING SYSTEM FOR REAL TIME EVALUATION OF POST-STROKE PHYSIOTHERAPY OUTCOMES (Kumbala Pradeep Reddy, S Jagadeesh B. Narendra Kumar , Trans.). (2024). Cuestiones De Fisioterapia, 53(03), 7531-7539. https://doi.org/10.48047/6c574f80