Estimation of the Average Gait Velocity based on Statistical Stride Parameters of Foot Sensor Data

Harald Loose, Katja Orlowski, Laura Tetzlaff

2016

Abstract

The paper deals with the estimation of gait parameters based on data acquired by inertial measurement units (IMU) placed at the middle foot (metatarsus). The developed method described in (Loose and Orlowski, 2015) is robust against a wide spectrum of the gait speed. The gait parameters (stride duration, length, velocity, distance) are calculated stride by stride with excellent quality. This paper is focused on experimental data acquired during walking on treadmill with a speed profile. First the robustness of the method is shown and quantified using statistical characteristics of each speed level and the whole walking distance. Second the determined speed profiles are evaluated against the adjusted speed profile and an alternative camera based measurement. Third the influence of the walking speed on various physical and statistical stride parameters is discussed. Fourth a model to estimate the walking speed as a function of the root mean square of the magnitude of the angular velocity vector is proposed and evaluated. The rms is calculated for the acquired sensor data after stride detection for the whole stride. The proposed method is applicable to any IMU applied to the metatarsus.

Paper Citation

in Harvard Style

Loose H., Orlowski K. and Tetzlaff L. (2016). Estimation of the Average Gait Velocity based on Statistical Stride Parameters of Foot Sensor Data . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 277-283. DOI: 10.5220/0005822602770283

in Bibtex Style

@conference{biosignals16,
author={Harald Loose and Katja Orlowski and Laura Tetzlaff},
title={Estimation of the Average Gait Velocity based on Statistical Stride Parameters of Foot Sensor Data},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016)},
year={2016},
pages={277-283},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005822602770283},
isbn={978-989-758-170-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2016)
TI - Estimation of the Average Gait Velocity based on Statistical Stride Parameters of Foot Sensor Data
SN - 978-989-758-170-0
AU - Loose H.
AU - Orlowski K.
AU - Tetzlaff L.
PY - 2016
SP - 277
EP - 283
DO - 10.5220/0005822602770283