A kinematic algorithm to identify gait events during running at different speeds and with different footstrike types
journal contributionposted on 02.11.2016 by Joe C. Handsaker, Steph Forrester, Jonathan Folland, Matthew Black, Sam Allen
Any type of content formally published in an academic journal, usually following a peer-review process.
Although a number of algorithms exist for estimating ground contact events (GCEs) from kinematic data during running, they are typically only applicable to heelstrike running, or have only been evaluated at a single running speed. The purpose of this study was to investigate the accuracy of four kinematics-based algorithms to estimate GCEs over a range of running speeds and footstrike types. Subjects ran over a force platform at a range of speeds; kinetic and kinematic data was captured at 1000 Hz, and kinematic data was downsampled to 250 Hz. A windowing process initially identified reduced time windows containing touchdown and toe-off. Algorithms based on acceleration and jerk signals of the foot markers were used to estimate touchdown (2 algorithms), toe-off (2 algorithms), and ground contact time (GCT) (4 algorithms), and compared to synchronous ‘gold standard’ force platform data. An algorithm utilising the vertical acceleration peak of either the heel or first metatarsal marker (whichever appeared first) for touchdown, and the vertical jerk peak of the hallux marker for toe-off, resulted in the lowest offsets (+3.1 ms, 95% Confidence Interval (CI): -11.8 to +18.1 ms; and +2.1 ms, CI: -8.1 to +12.2 ms respectively). This method also resulted in the smallest offset in GCT (-1.1 ms, CI: -18.6 to +16.4 ms). Offsets in GCE and GCT estimates from all algorithms were typically negatively correlated to running speed, with offsets decreasing as speed increased. Assessing GCEs and GCT using this method may be useful when a force platform is unavailable or impractical.
- Sport, Exercise and Health Sciences