Choice of Piezoelectric Element over Accelerometer for an Energy-Autonomous Shoe-Based System

Gogoi, Niharika; Zhu, Yuanjia; Kirchner, Jens; Fischer, Georg; Zhu, Yuanjia

Abstract

Shoe-based wearable sensor systems are a growing research area in health monitoring, disease diagnosis, rehabilitation, and sports training. These systems—equipped with one or more sensors, either of the same or different types—capture information related to foot movement or pressure maps beneath the foot. This captured information offers an overview of the subject’s overall movement, known as the human gait. Beyond sensing, these systems also provide a platform for hosting ambient energy harvesters. They hold the potential to harvest energy from foot movements and operate related low-power devices sustainably. This article proposes two types of strategies (Strategy 1 and Strategy 2) for an energy-autonomous shoe-based system. Strategy 1 uses an accelerometer as a sensor for gait acquisition, which reflects the classical choice. Strategy 2 uses a piezoelectric element for the same, which opens up a new perspective in its implementation. In both strategies, the piezoelectric elements are used to harvest energy from foot activities and operate the system. The article presents a fair comparison between both strategies in terms of power consumption, accuracy, and the extent to which piezoelectric energy harvesters can contribute to overall power management. Moreover, Strategy 2, which uses piezoelectric elements for simultaneous sensing and energy harvesting, is a power-optimized method for an energy-autonomous shoe system.

Citation

Gogoi, N., Zhu, Y., Kirchner, J., Fischer, G., & Zhu, Y. (2024). Choice of Piezoelectric Element over Accelerometer for an Energy-Autonomous Shoe-Based System. Sensors, 24(8), Article 2549. https://doi.org/10.3390/s24082549

• Journal Article Type: Article
• Acceptance Date: Apr 11, 2024
• Online Publication Date: Apr 16, 2024
• Publication Date: Apr 2, 2024
• Deposit Date: May 15, 2024
• Publicly Available Date: May 15, 2024
• Journal: Sensors
• Electronic ISSN: 1424-8220
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 8
• Article Number: 2549
• DOI: https://doi.org/10.3390/s24082549
• Keywords: activity recognition, piezoelectric, step-count, accelerometer, gait
• Public URL: https://durham-repository.worktribe.com/output/2437299