The University of Sheffield
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Data for the paper "A new proxy measurement algorithm with applications to estimation of vertical ground reaction forces using wearable sensors"

posted on 2017-08-30, 15:45 authored by Yuzhu Guo, Fabio StormFabio Storm, Yifan ZhaoYifan Zhao, Stephen Billings, Alex Pavic, Claudia Mazza, Lingzhong GuoLingzhong Guo

Guo, Y., Storm, F., Zhao, Y. et al. (2017) A new proxy measurement algorithm with application to the estimation of vertical ground reaction forces using wearable sensors. Sensors, 17 (10). 2181. ISSN 1424-8220. DOI:10.3390/s17102181

Measurement of the ground reaction forces (GRF) during walking is typically limited to laboratory settings and only short observations using wearable pressure insoles have been reported so far. In this study, a new proxy measurement method is proposed to estimate the vertical component of the GRF (vGRF) from wearable accelerometer signals. The accelerations are used as the proxy variable. An orthogonal forward regression algorithm (OFR) is employed to identify the dynamic relationships between the proxy variables and the measured vGRF using pressure-sensing insoles. The obtained model, which represents the connection between the proxy variable and the vGRF, is then used to predict the latter. The results have been validated using pressure insoles data collected from nine healthy individuals under two outdoor walking tasks in non-laboratory settings. Results show that the vGRFs can be reconstructed with high accuracy (with an average prediction error of less than 6%) using only one wearable sensor mounted at forehead level. Proxy measures with different sensor positions are also discussed. Results show that the forehead accelerations based proxy measurement is more stable with less inter-task and inter-subject variability than the proxy measures using cervical and low back level accelerations. The proposed proxy measure provides a promising low-cost method for monitoring ground reaction forces in real life settings and introduces a novel generic approach for replacing the direct determination of difficult to measure variables in many applications.


The research was funded by the UK Engineering and Physical Sciences Research Council (EP/K03877X/1).



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