Data-Driven Optimization of Sensor Placement for Pressure Insoles Using Particle Swarm Optimization

Zrenner M, Stöve M, Franklin S, Kumar B, Jensen U, Eskofier B (2022)


Publication Type: Book chapter / Article in edited volumes

Publication year: 2022

Publisher: Springer, Cham

Edited Volumes: Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference

Pages Range: 160-164

ISBN: 9783030993320

DOI: 10.1007/978-3-030-99333-7_27

Abstract

Commercial pressure insoles use a high number of small sensor elements for the in-field measurement of vertical ground reaction forces (VGRFs) with high spatial resolution. However, the energy demands and costs of these insoles are high. Thus, the use of a smaller sub-set of sensors is proposed by various authors. Thereby, the placement of the sensor elements is chosen based on anatomical landmarks of the foot. In this work, we investigate the optimal placement of a subset of sensor elements for the reconstruction of VGRFs using a data-driven approach based on particle swarm optimization. Results show, that a data-driven placement of the sensor elements reduces the root mean squared error of the reconstructed VGRFs compared to a sensor placement based on anatomical landmarks.

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How to cite

APA:

Zrenner, M., Stöve, M., Franklin, S., Kumar, B., Jensen, U., & Eskofier, B. (2022). Data-Driven Optimization of Sensor Placement for Pressure Insoles Using Particle Swarm Optimization. In Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference. (pp. 160-164). Springer, Cham.

MLA:

Zrenner, Markus, et al. "Data-Driven Optimization of Sensor Placement for Pressure Insoles Using Particle Swarm Optimization." Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference. Springer, Cham, 2022. 160-164.

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