Knowledge-Based Expert System for Orthopedic Injury Management With Integrated Transcutaneous Electrical Nerve Simulation Therapy.

Abstract

Orthotic treatment, particularly for ankle injuries, often relies on devices such as ankle-foot orthoses (AFOs) to support and stabilize the foot and ankle. Given the high prevalence of lower extremity injuries, especially in sports, and the diagnostic challenges faced by clinicians, there is a pressing need for intelligent systems that aid in accurate assessment and personalized management. Misdiagnosis and suboptimal treatment of ankle conditions, including fractures and sprains, can lead to long-term complications and hinder recovery. This study presents TeleOrtho, a knowledge-based expert system designed to provide personalized diagnosis, treatment recommendations, and recovery plans for ankle injuries, integrating transcutaneous electrical nerve stimulation (TENS) therapy to enhance rehabilitation. The system was implemented using Flutter for cross-platform deployment and Python for expert rule modeling, and it features a user-friendly interface for both clinicians and patients. Diagnostic accuracy and treatment pathways were validated through two published case scenarios, confirming the system's alignment with medical guidelines. Static and dynamic testing demonstrated consistent functionality, and initial usability assessment indicated high user satisfaction (average SUS score: 85.3/100). The expert system reliably identified injury types based on structured symptom input and suggested individualized recovery plans. These results affirm the potential of TeleOrtho to reduce diagnostic errors, improve therapy adherence, and enhance clinical decision-making. Future work will focus on integrating imaging analysis, expanding the knowledge base to include additional orthopedic conditions, and conducting clinical trials for broader validation.