AI-Enhanced TENS Therapy in Rehabilitation: Optimizing Pain Management and Functional Recovery through Data-Driven Approaches

Transcutaneous Electrical Nerve Stimulation (TENS) is a widely used technique for pain management and rehabilitation, but its effectiveness often depends on the personalization of treatment parameters. Artificial Intelligence (AI), through machine learning and real-time data analysis, has the potential to optimize TENS therapy by providing personalized, adaptive treatment regimens. This paper explores the integration of AI with TENS in rehabilitation, aiming to enhance pain relief, functional recovery, and treatment efficiency. A systematic review of existing literature is conducted to examine current applications of TENS and AI in clinical settings. Based on these findings, an AI-driven model for real-time TENS adjustment is proposed, which tailors stimulation parameters to individual patient needs. Theoretical predictions suggest that AI-enhanced TENS will lead to improved outcomes in pain management, reduced treatment times, and increased patient satisfaction compared to traditional methods. Future directions include clinical validation through pilot trials and further development of AI algorithms to enhance rehabilitation protocols. This research holds promise for revolutionizing rehabilitation by combining traditional therapies with advanced technologies to create more effective, personalized treatments.

کلیدواژه ها:

TENS ، Artificial Intelligence ، Pain Management ، Rehabilitation ، Personalized Treatment