Vision-based approach for long-term mobility monitoring: Single case study following total hip replacement.

This article presents a single case study on the feasibility of using a low-cost and portable vision-based system (a Microsoft Kinect sensor) to monitor changes in movement patterns before and after a total hip replacement surgery. The primary subject was a male older adult with total hip replacement who performed two different functional tasks: walking and sit-to-stand. The tasks were recorded with a Kinect multiple times, starting from 1 d before the surgery until 9 wk after the surgery. An automated algorithm has been developed to extract the important spatiotemporal characteristics from the video recorded functional tasks (walking and sit-to-stand). Statistical analysis was then performed by Tryon C statistic to study changes in spatiotemporal characteristics between different stages before and after the surgery. The statistical analysis indicated significant difference and slight improvement between all measures from the presurgery to each postsurgery date. The study confirmed that the Kinect sensor and an automated algorithm have the potential to be integrated into a patient's home to monitor changes in mobility during the recovery period.