Gait Assessment for Multiple Sclerosis Patients Using Microsoft Kinect
This work addresses gait assessment for multiple sclerosis patients, offering a low-cost solution for rehabilitation, but it is incremental as it builds on existing gait indices with new methods.
The researchers tackled gait analysis for multiple sclerosis patients by developing a framework using a Microsoft Kinect sensor to quantify gait abnormalities, introducing novel indices based on dynamic time warping to characterize gait patterns and measure distance from healthy populations, and establishing feasibility for clinical assessment.
Gait analysis of patients with neurological disorders, including multiple sclerosis (MS), is important for rehabilitation and treatment. The Mircrosoft Kinect sensor, which was developed for motion recognition in gaming applications, is an ideal candidate for an inexpensive system providing the capability for human gait analysis. In this research, we develop a framework to quantify the gait abnormality of MS patients using a Kinect for Windows camera. In addition to the previously introduced gait indices, a novel set of MS gait indices based on the concept of dynamic time warping is introduced. The newly introduced indices can characterize a patient's gait pattern as a whole and quantify a subject's gait distance from the healthy population. We will investigate the correlation of gait indices with the multiple sclerosis walking scale (MSWS) and the clinical ambulation score. This work establishes the feasibility of using the Kinect sensor for clinical gait assessment for MS patients.