Comparison of Different Algorithms for Calculating Velocity and Stride Length in Running Using Inertial Measurement Units

Beitrag in einer Fachzeitschrift
(Originalarbeit)


Details zur Publikation

Autor(en): Zrenner M, Gradl S, Jensen U, Ullrich M, Eskofier B
Zeitschrift: Sensors
Jahr der Veröffentlichung: 2018
Band: 18
Heftnummer: 12
ISSN: 1424-8220
Sprache: Englisch


Abstract

Running has a positive impact on human health and is an accessible sport
for most people. There is high demand for tracking running performance
and progress for amateurs and professionals alike. The parameters
velocity and distance are thereby of main interest. In this work, we
evaluate the accuracy of four algorithms, which calculate the stride
velocity and stride length during running using data of an inertial
measurement unit (IMU) placed in the midsole of a running shoe. The four
algorithms are based on stride time, foot acceleration, foot trajectory
estimation, and deep learning, respectively. They are compared using
two studies: a laboratory-based study comprising 2377 strides from 27
subjects with 3D motion tracking as a reference and a field study
comprising 12 subjects performing a 3.2-km run in a real-world setup.
The results show that the foot trajectory estimation algorithm performs
best, achieving a mean error of 0.032 ± 0.274 m/s for the velocity
estimation and 0.022 ± 0.157 m for the stride length. An interesting
alternative for systems with a low energy budget is the
acceleration-based approach. Our results support the implementation
decision for running velocity and distance tracking using IMUs embedded
in the sole of a running shoe.


FAU-Autoren / FAU-Herausgeber

Eskofier, Björn Prof. Dr.
Jensen, Ulf
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Stiftungs-Juniorprofessur für Sportinformatik (Digital Sports)
Gradl, Stefan
Ullrich, Martin
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Zrenner, Markus
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)


Zusätzliche Organisationseinheit(en)
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)


Zitierweisen

APA:
Zrenner, M., Gradl, S., Jensen, U., Ullrich, M., & Eskofier, B. (2018). Comparison of Different Algorithms for Calculating Velocity and Stride Length in Running Using Inertial Measurement Units. Sensors, 18(12). https://dx.doi.org/10.3390/s18124194

MLA:
Zrenner, Markus, et al. "Comparison of Different Algorithms for Calculating Velocity and Stride Length in Running Using Inertial Measurement Units." Sensors 18.12 (2018).

BibTeX: 

Zuletzt aktualisiert 2019-07-01 um 05:10