Quasi real-time gait event detection using shank-attached gyroscopes.
This article describes an ambulatory gait event detection method for long-term monitoring of walking. Aminian et al. [2] have developed an automatic gait event detection algorithm based on shank-attached gyroscope signals. However, this algorithm has a drawback in that it is post-processed. We propose a modified algorithm which detects foot initial and end contact timings using the same concept as in [2], but in quasi real-time. The utilization of the knowledge on gait sequence and peak angular acceleration realizes the quasi real-time detection. Furthermore, to be practical, the algorithm has been developed to ensure the robustness of detection (i.e., without missing the gait events in various speed conditions). Validation of the algorithm using footswitches shows that the algorithm detected the end contacts earlier (-8 ms) and the initial contacts later (19 ms) than the footswitch-based method.
Mechatronic Systems Engineering, School of Engineering Science, Simon Fraser University, 250-13450 102nd Avenue, Surrey, BC V3T 0A3, Canada. jkl25@sfu.ca
Jung Keun
JK
Lee
Edward J
EJ
Park
D000054:Acceleration; D000328:Adult; D000465:Algorithms; D001696:Biomechanical Phenomena; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
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