Analyzing dynamic EMG and VMG signals of respiratory muscles

Author

Mañanas, Miguel A. ; Fiz, José A. ; Morera, Josep ; Caminal, Pere

Author_Institution

Centre de Recerca en Enginyeria Biomedica, Univ. Politecnica de Catalunya, Barcelona, Spain

Volume

20

Issue

6

fYear

2001

Firstpage

125

Lastpage

132

Abstract

A promising technique is described for evaluating ventilatory disease by studying activity and fatigue in the sternocleidomastoid muscle. We analyze dynamic muscular function in time and frequency domains during two respiratory load tests at different levels of ventilation.

Keywords

Fourier transforms; electromyography; lung; medical signal processing; pneumodynamics; spectral analysis; time-frequency analysis; wavelet transforms; Choi-Williams distribution; Morlet wavelet; Wigner-Ville distribution; cross-correlation function; dynamic EMG signals; dynamic muscular function; inspiratory interval; muscle contraction; muscle fiber depolarization; respiratory load tests; respiratory muscles; scalogram; short-time Fourier transform; spectrogram; stationarity analysis; sternocleidomastoid muscle; surface electromyographic signals; time-frequency analysis; ventilatory disease; vibromyographic signals; Biomedical measurements; Diseases; Electromyography; Fatigue; Frequency; Instruments; Muscles; Pressure measurement; Signal analysis; Testing; Aged; Chronic Disease; Electromyography; Exertion; Forced Expiratory Volume; Humans; Male; Middle Aged; Models, Statistical; Muscle Fatigue; Pulmonary Disease, Chronic Obstructive; Reproducibility of Results; Respiratory Function Tests; Respiratory Muscles; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Statistics as Topic; Stochastic Processes; Vibration;

fLanguage

English

Journal_Title

Engineering in Medicine and Biology Magazine, IEEE

Publisher

ieee

ISSN

0739-5175

Type

jour

DOI

10.1109/51.982284

Filename

982284