Differences in running technique between runners with better and poorer running economy and lower and higher milage: An artificial neural network approach

Van Hooren B, Lennartz R, Cox M, Hoitz F, Plasqui G, Meijer K (2024)


Publication Type: Journal article

Publication year: 2024

Journal

Book Volume: 34

Issue: 3

DOI: 10.1111/sms.14605

Abstract

Background

Prior studies investigated selected discrete sagittal-plane outcomes (e.g., peak knee flexion) in relation to running economy, hereby discarding the potential relevance of running technique parameters during noninvestigated phases of the gait cycle and in other movement planes.


Purpose

Investigate which components of running technique distinguish groups of runners with better and poorer economy and higher and lower weekly running distance using an artificial neural network (ANN) approach with layer-wise relevance propagation.


Methods

Forty-one participants (22 males and 19 females) ran at 2.78 m∙s−1 while three-dimensional kinematics and gas exchange data were collected. Two groups were created that differed in running economy or weekly training distance. The three-dimensional kinematic data were used as input to an ANN to predict group allocations. Layer-wise relevance propagation was used to determine the relevance of three-dimensional kinematics for group classification.


Results

The ANN classified runners in the correct economy or distance group with accuracies of up to 62% and 71%, respectively. Knee, hip, and ankle flexion were most relevant to both classifications. Runners with poorer running economy showed higher knee flexion during swing, more hip flexion during early stance, and more ankle extension after toe-off. Runners with higher running distance showed less trunk rotation during swing.


Conclusion

The ANN accuracy was moderate when predicting whether runners had better, or poorer running economy, or had a higher or lower weekly training distance based on their running technique. The kinematic components that contributed the most to the classification may nevertheless inform future research and training.

Authors with CRIS profile

Involved external institutions

How to cite

APA:

Van Hooren, B., Lennartz, R., Cox, M., Hoitz, F., Plasqui, G., & Meijer, K. (2024). Differences in running technique between runners with better and poorer running economy and lower and higher milage: An artificial neural network approach. Scandinavian journal of medicine & science in sports, 34. https://doi.org/10.1111/sms.14605

MLA:

Van Hooren, Bas, et al. "Differences in running technique between runners with better and poorer running economy and lower and higher milage: An artificial neural network approach." Scandinavian journal of medicine & science in sports 34 (2024).

BibTeX: Download