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Estimation of ground reaction forces and ankle moment with multiple, low-cost sensors
School of Kinesiology,
University of Michigan, 401 Washtenaw Ave CCRB, Ann Arbor, MI, USA
Journal of NeuroEngineering and Rehabilitation 2015, 12:90
doi:10.1186/s12984-015-0081-x
The electronic version of this article is the complete one and can be found online at: http://www.jneuroengrehab.com/content/12/1/90
The electronic version of this article is the complete one and can be found online at: http://www.jneuroengrehab.com/content/12/1/90
Received: | 2 June 2015 |
Accepted: | 29 September 2015 |
Published: | 14 October 2015 |
© 2015 Jacobs and Ferris.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Abstract
Background
Wearable sensor systems can provide data for at-home gait analyses and input to controllers
for rehabilitation devices but they often have reduced estimation accuracy compared
to laboratory systems. The goal of this study is to evaluate a portable, low-cost
system for measuring ground reaction forces and ankle joint torques in treadmill walking
and calf raises.
Methods
To estimate the ground reaction forces and ankle joint torques, we developed a custom
instrumented insole and a tissue force sensor. Six healthy subjects completed a collection
of movements (calf raises, 1.0 m/s walking, and 1.5 m/s walking) on two separate days.
We trained artificial neural networks on the study data and compared the estimates
to a multi-camera motion system and an instrumented treadmill. We evaluated the relative
strength of each sensor by testing each sensor’s ability to predict the ankle joint
torque calculated from a reference inverse kinematics algorithm. We assessed model
accuracy through root mean squared error and normalized root mean square error. We
hypothesized that the estimation of the models would have normalized root mean square
error measures less than 10 %.
Results
For walking at 1.0 and walking at 1.5 m/s, the single-task, intra-day and multi-task,
intra-day predictions had normalized root mean square error less than 10 % for all
three force components and both center of pressure components. For the calf raise
task, the single-task, intra-day and multi-task, intra-day predictions had normalized
root mean square error less than 10 % for only the anterior-posterior center of pressure.
The multi-task, intra-day model had similar predictions to the single-task, intra-day
model. The normalized root mean square error of predictions from the insole sensor
alone were less than 10 % for walking at 1.0 m/s and 1.5 m/s. No sensor was sufficient
for the calf raise task. The combination of the insole sensor and the tendon sensor
had lower normalized root mean square error than the individual sensors for all three
tasks.
Conclusions
The proposed sensor system provided accurate estimates for five of the six components
of the ground reaction kinetics during walking at 1.0 and 1.5 m/s and one of the six
components during the calf raise task. The normalized root mean square error of the
predictions of the ground reaction forces were similar to published studies using
commercial devices. The proposed system of low-cost sensors can provide useful estimations
of ankle joint torque for both walking and calf raises for future studies in mobile
gait analysis.
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