Journal
SENSORS
Volume 21, Issue 22, Pages -Publisher
MDPI
DOI: 10.3390/s21227553
Keywords
orthopedics; pedicle screw; stability diagnosis; laser resonance frequency analysis
Funding
- JSPS KAKENHI [JP 19K04286, JP 20K14684]
- AMED [JP20hm0102077h0001, JP21hm0102077h0002]
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The study examines the initial stability of pedicle screws post orthopedic surgery and introduces a new diagnostic method called Laser Resonance Frequency Analysis (L-RFA). It expands on the previous research by analyzing the vibrational spectra of polyaxial screws for L-RFA diagnosis and proposes a machine learning-based analysis scheme. This new method accurately predicts the stability of polyaxial pedicle screws, offering a valuable tool for clinical implant stability diagnosis using L-RFA.
Evaluation of the initial stability of implants is essential to reduce the number of implant failures of pedicle screws after orthopedic surgeries. Laser resonance frequency analysis (L-RFA) has been recently proposed as a viable diagnostic scheme in this regard. In a previous study, L-RFA was used to demonstrate the diagnosis of implant stability of monoaxial screws with a fixed head. However, polyaxial screws with movable heads are also frequently used in practice. In this paper, we clarify the characteristics of the laser-induced vibrational spectra of polyaxial screws which are required for making L-RFA diagnoses of implant stability. In addition, a novel analysis scheme of a vibrational spectrum using L-RFA based on machine learning is demonstrated and proposed. The proposed machine learning-based diagnosis method demonstrates a highly accurate prediction of implant stability (peak torque) for polyaxial pedicle screws. This achievement will contribute an important analytical method for implant stability diagnosis using L-RFA for implants with moving parts and shapes used in various clinical situations.
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