A 3D-Printed Piezoelectric Microdevice for Human Energy Harvesting for Wearable Biosensors

Area of Science:

• Biomedical Engineering
• Materials Science
• Energy Harvesting

Background:

• Wearable biosensors are crucial for continuous physiological monitoring but rely on batteries, causing signal discontinuity and patient discomfort.
• Arterial pulsations offer a consistent source of mechanical energy that can be converted into electrical power.
• Existing energy harvesting solutions for wearables often lack integration and efficiency.

Purpose of the Study:

• To develop and evaluate a novel 3D-printed wearable energy harvesting platform powered by radial artery pulsations.
• To investigate the use of piezoelectric materials for scavenging mechanical energy from the human body.
• To create a sustainable power source for wearable biosensors, enhancing diagnostic continuity.

Main Methods:

• A 3D-printed wearable platform was designed and fabricated using fused filament fabrication (FFF).
• A piezoelectric disc and a thermoplastic polyurethane (TPU) film were integrated to form an air chamber for improved skin adhesion and component protection.
• Computational fluid dynamics (CFD) simulations using COMSOL Multiphysics were performed to model and optimize harvester performance.
• The influence of piezoelectric material, diameter, and geometrical parameters on electrical output was analyzed.

Main Results:

• A functional prototype of the wearable energy harvester was successfully developed.
• CFD simulations provided insights into the harvester's energy and power output parameters.
• Optimization of geometrical and material parameters led to improved electrical output.
• The study established a correlation between harvester skin fit and voltage generation.

Conclusions:

• The developed 3D-printed wearable platform effectively scavenges energy from arterial pulsations.
• This piezoelectric energy harvesting approach offers a promising solution for self-powered wearable biosensors.
• The technology has the potential to improve continuous health monitoring by eliminating battery-related interruptions.