New Robotic Tool Enhances Stroke Recovery Progress Tracking

A new robotic tool developed by a team of experts in computer science and biokinesiology could help stroke survivors more accurately track their recovery progress. Annually, more than 15 million people worldwide experience a stroke, with three-quarters grappling with issues such as arm and hand impairment, weakness, and paralysis. Breaking the habit known as arm nonuse or learned nonuse can improve strength and prevent injury, but determining how much a patient utilizes their weaker arm outside clinical settings is challenging. USC researchers have developed a robotic system designed to collect precise data on how stroke survivors use their arms spontaneously. The method uses a robotic arm to track 3D spatial information, and machine learning techniques generate an arm nonuse metric, which could help clinicians accurately assess a patient’s rehabilitation progress. A socially assistive robot (SAR) provides instructions and encouragement throughout the challenge. This novel combination of technologies can serve as a more accurate and more motivating process for stroke patient assessment.