Title :
Automatic classification of respiratory signals
Author :
Ning, Taikang ; Bronzino, Joseph D.
Author_Institution :
Dept. of Eng. & Comput. Sci., Trinity Coll., Hartford, CT, USA
Abstract :
The authors present an automatic classification algorithm which is used to classify respiratory signals into the following categories: (1) normal respiration, (2) respiration with artifacts, and (3) apnea. When the recorded signal is scored as respiration, respiration rate estimates are computed. Results obtained using pilot data show good agreement with the classifications obtained by manual scoring methods
Keywords :
medical diagnostic computing; pneumodynamics; apnea; automatic classification algorithm; manual scoring; normal respiration; respiration rate estimates; respiration with artifacts; respiratory signals; Classification algorithms; Computer science; Educational institutions; Frequency estimation; Noise measurement; Pediatrics; Rhythm; Signal processing algorithms; State estimation; Ventilation;
Conference_Titel :
Engineering in Medicine and Biology Society, 1989. Images of the Twenty-First Century., Proceedings of the Annual International Conference of the IEEE Engineering in
Conference_Location :
Seattle, WA
DOI :
10.1109/IEMBS.1989.95923
