Next Article in Journal
Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
Next Article in Special Issue
The Use of Wearable Sensor Technology to Detect Shock Impacts in Sports and Occupational Settings: A Scoping Review
Previous Article in Journal
On Asymptotic Efficiency of the M2M4 Signal-to-Noise Estimator for Deterministic Complex Sinusoids
Previous Article in Special Issue
Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review
Article

Limitations of Foot-Worn Sensors for Assessing Running Power

1
Institute of Exercise Training and Sport Informatics, Department of Cognitive and Team/Racket Sport Research, German Sport University Cologne, 50933 Cologne, Germany
2
Department of Intervention Research in Exercise Training, German Sport University Cologne, 50933 Cologne, Germany
3
School of Sport and Health Sciences, University of Brighton, Eastbourne BN20 7SR, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Silvia Fantozzi
Sensors 2021, 21(15), 4952; https://doi.org/10.3390/s21154952
Received: 7 June 2021 / Revised: 18 July 2021 / Accepted: 19 July 2021 / Published: 21 July 2021
(This article belongs to the Special Issue Feature Papers in Wearables Section 2021)
Running power as measured by foot-worn sensors is considered to be associated with the metabolic cost of running. In this study, we show that running economy needs to be taken into account when deriving metabolic cost from accelerometer data. We administered an experiment in which 32 experienced participants (age = 28 ± 7 years, weekly running distance = 51 ± 24 km) ran at a constant speed with modified spatiotemporal gait characteristics (stride length, ground contact time, use of arms). We recorded both their metabolic costs of transportation, as well as running power, as measured by a Stryd sensor. Purposely varying the running style impacts the running economy and leads to significant differences in the metabolic cost of running (p < 0.01). At the same time, the expected rise in running power does not follow this change, and there is a significant difference in the relation between metabolic cost and power (p < 0.001). These results stand in contrast to the previously reported link between metabolic and mechanical running characteristics estimated by foot-worn sensors. This casts doubt on the feasibility of measuring running power in the field, as well as using it as a training signal. View Full-Text
Keywords: accelerometer; running power; running economy; Stryd; metabolic cost of transportation accelerometer; running power; running economy; Stryd; metabolic cost of transportation
Show Figures

Figure 1

MDPI and ACS Style

Baumgartner, T.; Held, S.; Klatt, S.; Donath, L. Limitations of Foot-Worn Sensors for Assessing Running Power. Sensors 2021, 21, 4952. https://doi.org/10.3390/s21154952

AMA Style

Baumgartner T, Held S, Klatt S, Donath L. Limitations of Foot-Worn Sensors for Assessing Running Power. Sensors. 2021; 21(15):4952. https://doi.org/10.3390/s21154952

Chicago/Turabian Style

Baumgartner, Tobias, Steffen Held, Stefanie Klatt, and Lars Donath. 2021. "Limitations of Foot-Worn Sensors for Assessing Running Power" Sensors 21, no. 15: 4952. https://doi.org/10.3390/s21154952

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop