Article

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.

Langue : ANGLAIS