Acoustic emissions in vertebral cortical shell failure

Understanding the initiation of bony failure is critical in assessing the progression of bone fracture and in developing injury criteria. Detection of acoustic emissions in bone can be used to identify fractures more sensitively and at an earlier inception time compared to traditional methods. However, high rate loading conditions, complex specimen-device interaction or geometry may cause other acoustic signals. Therefore, characterization of the isolated local acoustic emission response from cortical bone fracture is essential to distinguish its characteristics from other potential acoustic sources. This work develops a technique to use acoustic emission signals to determine when cortical bone failure occurs by characterization using both a Welch power spectral density estimate and a continuous wavelet transform. Isolated cortical shell specimens from thoracic vertebral bodies with attached acoustic sensors were subjected to quasistatic loading until failure. The resulting acoustic emissions had a wideband frequency response with peaks from 20 to 900 kHz, with the spectral peaks clustered in three bands of frequencies (166 52.6 kHz, 379 +/- 37.2 kHz, and 668 +/- 63.4 kHz). Using these frequency bands, acoustic emissions can be used as a monitoring tool in biomechanical spine testing, distinguishing bone failure from structural response. This work presents a necessary set of techniques for effectively utilizing acoustic emissions to determine the onset of cortical bone fracture in biological material testing. Acoustic signatures can be developed for other cortical bone regions of interest using the presented methods. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Understanding the initiation of bony failure is crucial for assessing bone fracture progression. The use of acoustic emissions to identify fractures can provide more sensitivity than traditional methods. Differentiating bone failure from structural response in biomechanical testing can be achieved by characterizing localized acoustic emission responses.