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A Polymer-based Piezoelectric Vibration Energy Harvester with a 3D Meshed-Core Structure

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

Niharika Gogoi^1,2, Yuanjia Zhu², Jens Kirchner^2,3

¹Department of Computer Science, Durham University, Upper Mountjoy Campus, Stockton Road, Durham DH13LE, UK.

Sensors (Basel, Switzerland)

|April 27, 2024

Summary

This study compares two shoe-based sensor systems for gait analysis and energy harvesting. Strategy 2, using piezoelectric elements for both sensing and energy generation, offers a more power-optimized solution for autonomous wearable systems.

Keywords:

accelerometer activity recognition gait piezoelectric step-count

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Area of Science:

Biomedical Engineering
Wearable Technology
Energy Harvesting

Background:

Shoe-based wearable sensors are crucial for health monitoring, rehabilitation, and sports training.
These systems capture human gait data through foot movement and pressure sensing.
They also offer potential for harvesting energy from movement to power devices.

Purpose of the Study:

To propose and compare two strategies for energy-autonomous shoe-based sensor systems.
To evaluate the feasibility of using piezoelectric elements for simultaneous sensing and energy harvesting.
To assess power consumption, accuracy, and energy management contributions of each strategy.

Main Methods:

Strategy 1: Utilizes an accelerometer for gait acquisition and piezoelectric elements for energy harvesting.
Strategy 2: Employs piezoelectric elements for both gait sensing and energy harvesting.
Comparative analysis of power consumption, sensing accuracy, and energy harvesting efficiency.

Main Results:

Both strategies integrate piezoelectric elements for energy harvesting.
Strategy 2 demonstrates a power-optimized approach by using piezoelectric elements for dual functions.
A comprehensive comparison of power, accuracy, and energy management is presented.

Conclusions:

Strategy 2, leveraging piezoelectric elements for simultaneous sensing and energy harvesting, is a highly power-optimized method.
This approach advances the development of energy-autonomous shoe-based systems.
The findings pave the way for more sustainable wearable health monitoring solutions.