It can be a hassle to get to the doctor’s office. And the task can be especially challenging for parents of children with motor disorders such as cerebral palsy, as a clinician must evaluate the child in person on a regular basis, often for an hour at a time. Making it to these frequent evaluations can be expensive, time-consuming, and emotionally taxing.
MIT engineers hope to alleviate some of that stress with a new method that remotely evaluates patients’ motor function. By combining computer vision and machine-learning techniques, the method analyzes videos of patients in real-time and computes a clinical score of motor function based on certain patterns of poses that it detects in video frames.
The researchers tested the method on videos of more than 1,000 children with cerebral palsy. They found the method could process each video and assign a clinical score that matched with over 70 percent accuracy what a clinician had previously determined during an in-person visit.
