Gait quality evaluation method for post-stroke patients

Proliferation of low-cost nonintrusive wearable sensors enables researchers to explore capabilities in monitoring physiological parameters remotely expanding healthcare delivery and reducing costs. One of the parameters that is known to be important in rehabilitation and exercise physiology is human motion monitoring, such as analysis of the walking gait and corresponding characteristics. This paper presents a robust on-line methodology for computing clinically relevant metrics for assessing quality of the walking gait in normal subjects and subjects with gait abnormalities, e.g. in patients with stroke. Furthermore, this paper proposes a metric vector that enables characterization of spatiotemporal features of walking quality evolution for post-stroke patients during and after rehabilitation. This method enables visualization of the gait improvement or changes as a result of the rehabilitation or other treatment techniques.