AI-Driven Rehabilitation Robots: Enhancing Physical Therapy for Stroke and Injury Recovery

Abstract

AI-driven rehabilitation robots are transforming physical therapy by providing personalized, precise, and adaptive support for patients recovering from strokes and injuries. This research explores the integration of Artificial Intelligence (AI) into robotic systems to enhance physical rehabilitation outcomes, focusing on key areas such as motor skill recovery, real-time performance tracking, and patient engagement. Utilizing machine learning algorithms and biomechanical data, these robots can tailor therapy sessions to individual needs, dynamically adjusting resistance, movement patterns, and feedback. Advanced sensor technology enables the robots to monitor patient progress, ensuring accurate assessments and adaptive interventions. This study also examines the role of AI in promoting neuroplasticity through repetitive, task-specific training, a critical component of stroke recovery. Ethical considerations, including data privacy and accessibility, are analyzed to address barriers to widespread adoption. By bridging robotics, AI, and clinical practice, this research highlights the potential of AI-driven rehabilitation robots to revolutionize physical therapy, offering scalable and effective solutions that improve recovery rates and enhance the quality of care.