Breath detection using fuzzy sets and sensor fusion

Author

Cohen, Kevin P. ; Webster, John G. ; Northern, James ; Hu, Yu H. ; Tompkins, Willis J.

Author_Institution

Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA

fYear

1994

fDate

1994

Firstpage

1067

Abstract

We developed a breath detection algorithm which uses fuzzy sets to classify signals from multiple noninvasive sensing technologies. We tested our algorithm using simultaneous recordings from impedance and inductance plethysmographs, while healthy adults performed several different combinations of ventilation and motion. For 4 subjects, the average rates of false positive and false negative detection were 0.6% and 2.2%, respectively

Keywords

pneumodynamics; biomedical classification; breath detection algorithm; false negative detection; false positive detection; fuzzy sets; healthy adults; impedance plethysmographs; inductance plethysmographs; multiple noninvasive sensing technologies; sensor fusion; signal classification; ventilation; Abdomen; Belts; Detection algorithms; Electrodes; Fuzzy sets; Impedance measurement; Inductance measurement; Inference algorithms; Sensor fusion; Ventilation;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE

Conference_Location

Baltimore, MD

Print_ISBN

0-7803-2050-6

Type

conf

DOI

10.1109/IEMBS.1994.415327

Filename

415327