A novel kinematic detection of foot-strike and toe-off events during noninstrumented treadmill running to estimate contact time.

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License: CC BY-NC-ND 4.0
Serval ID
serval:BIB_BD614F5237AA
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A novel kinematic detection of foot-strike and toe-off events during noninstrumented treadmill running to estimate contact time.
Journal
Journal of biomechanics
Author(s)
Patoz A., Lussiana T., Gindre C., Malatesta D.
ISSN
1873-2380 (Electronic)
ISSN-L
0021-9290
Publication state
Published
Issued date
06/09/2021
Peer-reviewed
Oui
Volume
128
Pages
110737
Language
english
Notes
Publication types: Journal Article
Publication Status: aheadofprint
Abstract
Contact time (t <sub>c</sub> ) relies upon the accuracy of foot-strike and toe-off events, for which ground reaction force (GRF) is the gold standard. However, force plates are not always available, e.g., when running on a noninstrumented treadmill. In this situation, a kinematic algorithm (KA) - an algorithm based on motion capture data - might be used if it performs equally for all foot-strike angles across speeds. The purpose of this study was to propose a novel KA, using a combination of heel and toe kinematics (three markers per foot), to detect foot-strike and toe-off and compare it to GRF at different speeds and across foot-strike angles. One hundred runners ran at 9 km/h, 11 km/h, and 13 km/h. Force data and whole-body kinematic data were acquired by an instrumented treadmill and optoelectronic system. Foot-strike and toe-off showed small systematic biases between GRF and KA at all speeds (≤5 ms), except toe-off at 11 km/h (no bias). The root mean square error (RMSE) was ≤9 ms and was mostly constant across foot-strike angles for toe-off (7.4 ms) but not for foot-strike (4.1-11.1 ms). Small systematic biases (≤8 ms) and significant differences (P ≤ 0.01) were reported for t <sub>c</sub> at all speeds, and the RMSE was ≤14 ms (≤5%). The RMSE for t <sub>c</sub> increased with increasing foot-strike angle (3.5-5.4%). Nonetheless, this novel KA computed smaller errors than existing methods for foot-strike, toe-off, and t <sub>c</sub> . Therefore, this study supports the use of this novel KA to accurately estimate foot-strike, toe-off, and t <sub>c</sub> from kinematic data obtained during noninstrumented treadmill running independent of the foot-strike angle.
Keywords
Rehabilitation, Biomedical Engineering, Orthopedics and Sports Medicine, Biophysics, Event detection, Forefoot running, Gait analysis, Gait events, Midfoot running, Rearfoot running
Pubmed
Open Access
Yes
Create date
07/09/2021 17:28
Last modification date
22/09/2021 6:38
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