Breath detection using fuzzy sets and sensor fusion

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 ve...

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Bibliographic Details
Published inProceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society : engineering advances, new oportunities for biomedical engineers : Baltimore, Maryland, USA, November 3-6, 1994 Vol. 2; pp. 1067 - 1068 vol.2
Main Authors Cohen, K.P., Webster, J.G., Northern, J., Hu, Yu.H., Tompkins, W.J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1994
Subjects
Abdomen
Belts
Detection algorithms
Electrodes
Fuzzy sets
Impedance measurement
Inductance measurement
Inference algorithms
Sensor fusion
Ventilation
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ISBN9780780320505
0780320506
DOI10.1109/IEMBS.1994.415327

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Summary: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.
ISBN:9780780320505
0780320506
DOI:10.1109/IEMBS.1994.415327