ArticleMedical science monitor : international medical journal of experimental and clinical research2019
Drilling Condition Identification Based on Sound Pressure Signal in Anterior Cervical Discectomy Surgery.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- State-of-the-Art of Non-Radiative, Non-Visual Spine Sensing with a Focus on Sensing Forces, Vibrations and Bioelectrical Properties: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Dura Vibration Difference Between PTP Bone Resection and Upper Facet Joints En Bolc Resection in Posterior Thoracic Decompression.Orthopaedic surgery · 2025Article
- Identification of milling status based on vibration signals using artificial intelligence in robot-assisted cervical laminectomy.European journal of medical research · 2023Article
- Surgical Tool Handle Vibration-Based Drilling State Recognition During Hip Fracture Fixation.Orthopaedic surgery · 2022Article
- Biomechanical Study of Cervical Endplate Removal on Subsidence and Migration in Multilevel Anterior Cervical Discectomy and Fusion.Asian spine journal · 2022Article
- Motor Bur Milling State Identification via Fast Fourier Transform Analyzing Sound Signal in Cervical Spine Posterior Decompression Surgery.Orthopaedic surgery · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND In anterior cervical discectomy and fusion (ACDF) surgery, drilling operation causes a high risk of tissue injury. This study aimed to present a novel feedback system based on sound pressure signals to identify drilling condition during ACDF. MATERIAL AND METHODS ACDF surgery was performed on the C4/5 segments of 6 porcine cervical specimens. The annulus fibrosus, endplate cartilage, sub-endplate cortical bone, and posterior longitudinal ligament (PLL) were drilled until penetration using a 2-mm high-speed burr. Sound pressure signals were collected using a microphone and dynamic signal analyzer. The recorded signals of different tissues were proceeded with lifting wavelet transform for extracting harmonic components. The frequencies of harmonic components are 1, 2, 3, 4, and 5 times higher than the motor frequency. The magnitude of harmonic components was calculated to identify different drilling conditions, along a broad spectrum of frequencies (1-5 kHz). For statistical analysis, one-way ANOVA (analysis of variance) and post hoc test (Dunnett's T3) were performed. RESULTS Very good demarcation was found among the signal magnitudes of different drilling conditions. Different drilling conditions do not present the same rate of variation of frequency. Differences in magnitude among all drilling conditions were statistically significant at certain frequency points (p<0.05). In 3 cases, one tissue could not be identified with respect to another (annulus fibrosus and endplate cartilage at 2 kHz, PLL and penetration at 3 kHz, annulus fibrosus and sub-endplate cortical bone at 5 kHz, p>0.05). CONCLUSIONS Sound pressure signals may provide an auxiliary feedback system for enhancing drilling operation in ACDF surgery, especially in minimally invasive surgery.
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