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Applications and Comparison of Continuous Wavelet Transforms on Analysis of A-wave Impulse Noise

Qin J., Sun P.

Archives of Acoustics

2015

Vol. 40, No. 4

503--512

Noise induced hearing loss (NIHL) is a serious occupational related health problem worldwide. The A-wave impulse noise could cause severe hearing loss, and characteristics of such kind of impulse noise in the joint time-frequency (T-F) domain are critical for evaluation of auditory hazard level. This study focuses on the analysis of A-wave impulse noise in the T-F domain using continual wavelet transforms. Three different wavelets, referring to Morlet, Mexican hat, and Meyer wavelets, were investigated and compared based on theoretical analysis and applications to experimental generated A-wave impulse noise signals. The underlying theory of continuous wavelet transform was given and the temporal and spectral resolutions were theoretically analyzed. The main results showed that the Mexican hat wavelet demonstrated significant advantages over the Morlet and Meyer wavelets for the characterization and analysis of the A-wave impulse noise. The results of this study provide useful information for applying wavelet transform on signal processing of the A-wave impulse noise.

Influence of upper extremity position on EMG signal measures calculated in time, frequency and time-frequency domains

Wang J., Bartuzi P., Roman-Liu D.

Acta of Bioengineering and Biomechanics

2013

Vol. 15, no. 4

83--91

The aim of this study was to investigate the relationship between time-frequency, time and frequency measures when considering various upper extremity positions below the level of the shoulder and in trapezius as well as deltoideus muscles. During the experiment, 15 subjects performed a task that involved screwing and unscrewing a screw cap on a board in six different locations, i.e., there were six upper extremity positions. Variables were calculated in the time, frequency and time-frequency domains on a recorded EMG signal. The results showed that parameters analyzed in the time-frequency domain were more sensitive to changes in position than parameters analyzed in the frequency domain.