Feature Extraction From Wavelet Coefficients for Pattern Recognition Tasks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Time--frequency feature representation using energy concentration: An overview of recent advances
Digital Signal Processing
On the Complexity of Finite Sequences
IEEE Transactions on Information Theory
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Multimedia Signals and Systems
Multimedia Signals and Systems
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Cervical auscultation (CA) is an emerging method of assessing swallowing disorders that is both non-invasive and inexpensive. This technique utilizes microphones to detect acoustic sounds produced by swallowing activity and characterize its behavior. Though some properties of swallowing sounds are known, there is still a need for a complete understanding of the baseline characteristics of cervical auscultation signals as well as how they change due to the patient's head motion, age, and sex. In order to examine these parameters, data was collected from 56 healthy adult participants that performed six different head movement tasks without swallowing. After preprocessing the signal, features were extracted. Dependent variables were time domain, frequency domain and time-frequency domain features. Statistical tests showed that only the skewness and peak frequency were not statistically different for all tasks. The peak frequency results indicate that head movement does not significantly affect the microphone signal, and that it is unnecessary to filter out the lowest frequency components. No sex differences were observed in the extracted features, but several features exhibited age dependence.