Low latency breathing frequency detection and monitoring on a personal computer

We demonstrate a low latency respiratory/breathing frequency detection system that is fast (<5 ms), easy to operate, requires no batteries or external power supply and operates fully via computer-standard USB connection. Exercises in controlling ones breathing frequency, usually referred to as pa...

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Bibliographic Details
Published inJournal of medical engineering & technology Vol. 35; no. 6-7; pp. 322 - 329
Main Authors Leskovsek, Matevz, Ahlin, Dragomira, Cancer, Rok, Hosta, Milan, Enova, Dusan, Pusenjak, Nika, Bunc, Matjaz
Format Journal Article
LanguageEnglish
Published England Informa Healthcare 01.10.2011
Taylor & Francis
Subjects
Adult
Aged
Algorithms
asthma
Breathing Exercises
breathing frequency detection
Equipment Design
Female
heart rate variability
Humans
hypertension
Male
Microcomputers
Middle Aged
Monitoring, Physiologic - instrumentation
Monitoring, Physiologic - methods
Respiration
Respiratory Mechanics - physiology
respiratory sinus arrhythmia
Sensitivity and Specificity
Signal Processing, Computer-Assisted - instrumentation
Software
Online AccessGet full text
ISSN0309-1902
1464-522X
1464-522X
DOI10.3109/03091902.2011.591481

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Summary:We demonstrate a low latency respiratory/breathing frequency detection system that is fast (<5 ms), easy to operate, requires no batteries or external power supply and operates fully via computer-standard USB connection. Exercises in controlling ones breathing frequency, usually referred to as paced-breathing exercises, have shown positive effects in treating pulmonary diseases, cardiovascular diseases and stress/anxiety-related disorders. We developed a breathing frequency detection system which uses two pairs of microphones to detect exhalation activity, eliminate noise from the environment and stream the recording data via USB connection to a personal computer. It showed 97.1% reliability (10 subjects) when monitoring breathing activity in non-guided free breathing and 100% reliability (10 subjects) when monitoring breathing activity during interactive paced-breathing exercises. We also evaluated the breathing frequency detection systems noise elimination functionality which showed a reduction of 84.2 dB for stationary (white noise) and a reduction of 79.3 dB for non-stationary (hands clapping) noise.
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ISSN:0309-1902
1464-522X
1464-522X
DOI:10.3109/03091902.2011.591481