Extracting cervical spine popping sound during neck movement and analyzing its frequency using wavelet transform

Abstract

With the excessive use of smartphones, cervical spine pain is becoming increasingly prevalent. A denoised cervical spine popping sound can aid in monitoring and estimating the state of the cervical spine. However, cervical spine popping sounds that are collected when a subject performs neck movements is contaminated by constant noise. Therefore, a denoising algorithm called Wavelet Transform-Based Stationary-Nonstationary (WTST-NST) is adopted to remove the noise. The input signal is decomposed using wavelet transform to obtain the wavelet coefficients. The wavelet coefficients are then separated into two parts, the nonstationary part and the stationary part, using stationary-nonstationary filtering technology. Finally, the wavelet coefficients of the nonstationary part are reconstructed to obtain the denoised cervical spine popping sound. In addition, the frequency components of the sound are analyzed using the multiresolution analysis of the wavelet transform. The experimental results demonstrate that the implementation of the WTST-NST algorithm in the sound analysis of cervical spine facet joints efficiently reduces the overlapped noise, producing an almost pure cervical spine popping sound. Furthermore, the frequency components of cervical spine popping sounds during the smartphone use period are significantly higher than that in the non-use period and are significantly associated with self-reported neck and upper back pain during the smartphone use period. Therefore, the WTST-NST algorithm preserved almost all the features of the sampled input signal. The denoised cervical spine popping sound can be used to quickly and conveniently monitor the status of the cervical spine during the smartphone use period.