Research Article
MyWalk: A Mobile App for Gait Asymmetry Rehabilitation in the Community
@INPROCEEDINGS{10.4108/icst.pervasivehealth.2013.252118, author={Tuck-Voon How and Justin Chee and Eric Wan and Alex Mihailidis}, title={MyWalk: A Mobile App for Gait Asymmetry Rehabilitation in the Community}, proceedings={7th International Conference on Pervasive Computing Technologies for Healthcare}, publisher={IEEE}, proceedings_a={PERVASIVEHEALTH}, year={2013}, month={5}, keywords={biofeedback contextual rehabilitation technologies gait outpatient rehabilitation smartphones stroke step-time asymmetry}, doi={10.4108/icst.pervasivehealth.2013.252118} }- Tuck-Voon How
Justin Chee
Eric Wan
Alex Mihailidis
Year: 2013
MyWalk: A Mobile App for Gait Asymmetry Rehabilitation in the Community
PERVASIVEHEALTH
ICST
DOI: 10.4108/icst.pervasivehealth.2013.252118
Abstract
MyWalk is a mobile app to enable gait rehabilitation in the community. Particularly, it can be used to treat and assess step-time asymmetry (STA) - which occurs when the amount of time between consecutive heel strikes is uneven. Temporal gait asymmetry, of which STA is a form, is common post-stroke and could result in difficulties such as joint degeneration or musculoskeletal pain. By enabling STA rehabilitation on a smartphone, post-stroke patients can now improve and assess their STA within the context of their everyday environments. Initial validation of MyWalk's algorithm showed minimal error (RMSE 2.20-2.67%) versus a foot-switch ground truth in detecting STA for symmetric walking conditions, but larger error (RMSE 13.82-16.34%) in asymmetric walking conditions. Future work will be to improve the accuracy of MyWalk's STA algorithm.
