Performance of a passive, wireless, resonant force sensor for smart orthopedic implants

Authors
Schroeder, Dustin
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Other Contributors
Ledet, Eric H.
Chan, Deva
Thompson, Deanna M.
Issue Date
2020-08
Keywords
Biomedical engineering
Degree
MS
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
Our wireless, passive resonant force sensors are composed of two mirrored, parallel, Archimedean spiral coils separated by a solid insulating dielectric material that deforms in response to an applied load. An axial load causes a deformation in the intervening dielectric layer, changing the mutual capacitive and inductive interactions between the coils. This change in electrical behavior results in a measurable change in resonant frequency which correlates to the applied load.
We built a model that can be used by researchers and engineers to design and build passive resonant force sensors for smart orthopedic implants. We developed techniques for rapid and inexpensive fabrication of passive resonant sensors. We also successfully demonstrated real-time, wireless force sensing with rapidly prototyped, PCB-based, resonant force sensors designed via the model. This predictive model will be a useful tool for medical researchers and engineers to determine whether their smart orthopedic implants utilizing these novel wireless, passive, resonant force sensors will function as needed.
Results showed that the model accurately predicted the resonant frequency of coils and air sensors over a wide range of geometries and configurations. The analytical model was further validated through measurement of solid force sensor behavior under compression. The model accurately predicted the resonant frequencies of fabricated force sensors, and the sensors exhibited high sensitivity to applied loads while remaining within predefined, physiologically relevant design constraints.
Low cost, rapid prototyping of force sensors was enabled through use of printed circuit board (PCB)-based coils. PCB coils are simple and quick to batch produce and were used to fabricate a wide array of sensor geometries to test against the model for validation. Parylene C was used as an intervening layer due to its material properties and unique, conformal deposition process. These combined manufacturing techniques allowed us to produce high-quality force sensors that were able to accurately measure physiologically relevant loading conditions.
Smart orthopedic implants are invaluable tools for elucidating physiologically relevant data in vivo. These data can be used to validate biomechanical models and to improve implant designs. Smart spinal fusion implants could provide insight into the mechanisms of degenerative disc disease (DDD), as well as the role of biomechanics in the fusion healing process.
Due to the size constraints and complexity of the lower cervical spine, nobody has successfully measured the forces passing through the interbody disc space in the cervical spine in vivo. Wireless, passive resonant force sensors may provide an alternative to conventional sensor technology such as strain gages used to measure loads. Wireless, passive resonant force sensors are low cost, have a small footprint, are durable, and are simple, making them an attractive alternative for instrumenting a smart cervical interbody implant.
In this research, a predictive model of passive resonant force sensor behavior was developed as a tool to efficiently and rapidly design force sensors for various smart orthopedic implant applications. More specifically, this model was used to develop wireless, passive resonant force sensors for use in a cervical interbody implant.
Description
August 2020
School of Engineering
Department
Dept. of Biomedical Engineering
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.