An AI-Based Neural Network Approach for Post-Surgical Elbow Exercise Recommendation

Abstract

Postoperative rehabilitation after elbow surgery is essential for recovering functionality, alleviating discomfort, and averting long-term problems. This work presents an artificial intelligence-driven recommendation system aimed at aiding doctors in the selection of effective rehabilitation exercises for patients recovering from different forms of elbow surgery. A Deep Neural Network (DNN) model was implemented and trained using a dataset that included variables such as kind of surgery type, pain location, range of motion (ROM), and comorbidities. The DNN exhibited exceptional prediction accuracy in determining the most appropriate activities for specific patients. This method facilitates individualized treatment planning, improves clinical decision-making at the bedside, alleviates the strain of physiotherapists, and fosters more efficient and flexible recovery procedures.

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