Title :
MyWalk: A mobile app for gait asymmetry rehabilitation in the community
Author :
Tuck-Voon How ; Chee, J. ; Wan, Elaine ; Mihailidis, Alex
Author_Institution :
Inst. of Biomater. & Biomed. Eng., Univ. of Toronto, Toronto, ON, Canada
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.
Keywords :
gait analysis; medical computing; mobile computing; patient rehabilitation; smart phones; MyWalk´s STA algorithm; RMSE; STA rehabilitation; asymmetric walking conditions; common post-stroke; consecutive heel strikes; foot-switch ground truth; joint degeneration; mobile application; musculoskeletal pain; post-stroke patients; smartphone; step-time asymmetry; symmetric walking conditions; temporal gait asymmetry rehabilitation; Joints; Legged locomotion; Noise; biofeedback; contextual rehabilitation technologies; gait; outpatient rehabilitation; smartphones; step-time asymmetry; stroke;
Conference_Titel :
Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2013 7th International Conference on
Conference_Location :
Venice
Print_ISBN :
978-1-4799-0296-5
Electronic_ISBN :
978-1-936968-80-0
