Journal of Advances in Developmental Research

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AI-Driven Physiotherapy Scheduling for Obesity Treatment: Optimizing Exercise-Based Rehabilitation Programs

Author(s) V.V. Manjula Kumari
Country United States
Abstract Effective physiotherapy is essential for managing obesity-related mobility issues and improving functional move- ment in overweight individuals. However, challenges in reha- bilitation scheduling often limit the accessibility of tailored exercise programs. In this paper, I propose an AI-powered phys- iotherapy scheduling framework that optimizes obesity-focused rehabilitation programs by efficiently assigning therapists, gym resources, and patient sessions. The system utilizes Answer Set Programming (ASP) to streamline exercise scheduling for obese patients, ensuring consistency in treatment, therapist allocation, and optimal session timing. The scheduling model incorporates patient preferences, obesity-specific rehabilitation constraints, and session optimization strategies. I apply the framework to real-world physiotherapy centers, demonstrating its effectiveness in enhancing accessibility and adherence to weight-loss physiotherapy programs. Experimental results show that the AI-driven scheduling system improves session availability, reduces therapist workload imbalance, and enhances rehabilitation efficiency. This research highlights the potential of AI in optimizing physiotherapy planning for obesity treatment, ensuring more structured and accessible exercise-based interventions.
Field Engineering
Published In Volume 15, Issue 2, July-December 2024
Published On 2024-08-09
Cite This AI-Driven Physiotherapy Scheduling for Obesity Treatment: Optimizing Exercise-Based Rehabilitation Programs - V.V. Manjula Kumari - IJAIDR Volume 15, Issue 2, July-December 2024. DOI 10.71097/IJAIDR.v15.i2.1444
DOI https://doi.org/10.71097/IJAIDR.v15.i2.1444
Short DOI https://doi.org/g9q35j
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