Abstract
Effective contact () and flight () times, instead of ground contact () and flight () times, are usually collected outside the laboratory using inertial sensors. Unfortunately, and cannot be related to and because the exact shape of vertical ground reaction force is unknown. However, using a sine wave approximation for vertical force, and as well as and could be related. Indeed, under this approximation, a transcendental equation was obtained and solved numerically over a grid. Then, a multivariate polynomial regression was applied to the numerical outcome. In order to reach a root-mean-square error of 0.5 ms, the final model was given by an eighth-order polynomial. As a direct application, this model was applied to experimentally measured values. Then, reconstructed (using the model) was compared to corresponding experimental ground truth. A systematic bias of 35 ms was depicted, demonstrating that ground truth values were larger than reconstructed ones. Nonetheless, error in the reconstruction of from was coming from the sine wave approximation, while the polynomial regression did not introduce further error. The presented model could be added to algorithms within sports watches to provide robust estimations of and in real time, which would allow coaches and practitioners to better evaluate running performance and to prevent running-related injuries.
Highlights
Ground contact and flight times are key temporal parameters of running biomechanics
The polynomial which provided an root-mean-square error (RMSE) smaller than 0.5 ms was kept as the final model of choice (RMSE 0.43 ms; R2 99.99%) and corresponded to a polynomial model including up to eighth-order terms [P8(tce, tfe), Eq 3]
In the case where an algorithm based on effective timings is running on the fly to provide live feedbacks, such as in sports watches, one could add the proposed model in the end of the algorithm chain, right before computing the biomechanical outcomes
Summary
Ground contact (tc) and flight (tf) times are key temporal parameters of running biomechanics. Alternatives would be to use a motion capture system (Lussiana et al, 2019; Patoz et al, 2020) or a light-based optical technology (Debaere et al, 2013) Even though these three systems can be used outside the laboratory (Purcell et al, 2006; Hébert-Losier et al, 2015; Ammann et al, 2016; Lussiana and Gindre, 2016), they suffer a lack of portability and are restricted to a specific and small capture volume, that is, they do not allow continuous temporal gait data collection throughout the entire training or race. Techniques to identify FS and TO events were developed using portative tools such as inertial measurement units (IMUs), which are easy to use, low cost, and suitable for field measurements and very practical to use in a coaching environment (Camomilla et al, 2018)
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