Breathing detection: towards a miniaturized, wearable, battery-operated monitoring system.
This paper analyzes the main challenges associated with noninvasive, continuous, wearable, and long-term breathing monitoring. The characteristics of an acoustic breathing signal from a miniature sensor are studied in the presence of sources of noise and interference artifacts that affect the signal. Based on these results, an algorithm has been devised to detect breathing. It is possible to implement the algorithm on a single integrated circuit, making it suitable for a miniature sensor device. The algorithm is tested in the presence of noise sources on five subjects and shows an average success rate of 91.3% (combined true positives and true negatives).
Corbishley
Phil
P
Department of Electrical and Electronic Engineering, Imperial College London, UK.
Rodríguez-Villegas
Esther
E
D000162:Acoustics / Q000295:instrumentation*; D001314:Auscultation / Q000295:instrumentation* / Q000379:methods; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D011211:Electric Power Supplies; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D008904:Miniaturization; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D015656:Respiratory Mechanics / Q000502:physiology*; D012135:Respiratory Sounds / Q000502:physiology*; D013018:Sound Spectrography / Q000295:instrumentation* / Q000379:methods; D014159:Transducers