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Innovations

Design considerations for piezocomposite materials for electrical stimulation in medical implants

, , , &
Pages 402-414 | Received 17 Jun 2021, Accepted 18 May 2022, Published online: 08 Jun 2022
 

Abstract

Incidence of non-union following long bone fracture fixation and spinal fusion procedures is increasing, and very costly for patients and the medical system. Direct current (DC) electrical stimulation has shown success as an adjunct therapy to stimulate bone healing and increase surgery success rates, though drawbacks of current devices and implantable battery packs have limited widespread use. Energy harvesting utilising piezoelectric materials has been widely studied for powering devices without a battery, and a preclinical animal study has shown efficacy of a piezocomposite spinal fusion implant resulting in faster, more robust fusion. Most piezoelectric energy harvesters operate most effectively at high frequencies, limiting power generation from loads experienced by orthopaedic implants during human motion. This work characterises the efficient power generation capability of a novel composite piezoelectric material under simulated walking loads. Building on compliant layer adaptive composite stacks (CLACS), the power generation of mixed-mode CLACS (MMCLACS) is defined. Utilising poling direction to capitalise on in-plane strain generation due to compliant layer expansion, MMCLACS significantly increased power output compared to a standard piezo stack. The combination of radial and through-thickness poled piezoelectric elements within a stack to create MMCLACS significantly increases power generation under low-frequency dynamic loads. This technology can be adapted to a variety of architectures and assembled as a load-bearing energy harvester within current implants. MMCLACS integrated with implants would provide enough power to deliver bone healing electrical stimulation directly to the fusion site, decreasing non-union rates, and also could provide quantitative assessment of healing progression through load sensing.

Acknowledgements

The authors also thank Madison and Lila Self Graduate Fellowship for generous support of graduate research at The University of Kansas.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Institute of Arthritis and Musculoskeletal and Skin Diseases.

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