Integrating artificial intelligence in physical therapy: a quasi-experimental study comparing conventional treatment with a hybrid intervention using telerehabilitation for workers with whiplash syndrome

Abstract

INTRODUCTION: AI-assisted telerehabilitation enables remote assessment and monitoring of patient movement, improving access to treatment while reducing costs. This study aimed to compare conventional center-based physical therapy with a hybrid intervention that combines face-to-face physiotherapy and AI-supervised telerehabilitation in workers affected by cervical whiplash syndrome. METHODS: The study population comprised workers aged 16 to 65 years requiring physical therapy for cervical whiplash syndrome (ICD-10 S13.4XXA). The primary outcome was the number of face-to-face sessions, while sickness absence duration was also analyzed. The sample included 15 patients in the telerehabilitation group and 28 in the conventional treatment group. The intervention included AI-supervised therapeutic exercises on days when patients received treatment at home, whereas on days they attended the rehabilitation center, they received the same standard treatment as the control group. RESULTS: The median number of face-to-face sessions was significantly lower in the telerehabilitation group (6 vs. 9), with differences remaining significant after adjustment. The duration of sickness absence was not longer in the telerehabilitation group (18 vs. 21 days). CONCLUSION: Reducing the number of face-to-face sessions through AI-assisted telerehabilitation optimizes physiotherapy resource utilization without prolonging sickness absence, thereby enhancing healthcare efficiency.

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