Quantifying respiratory variation with force sensor measurements

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http://hdl.handle.net/10138/39230

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Paalasmaa , J , Leppäkorpi , L & Partinen , M 2011 , Quantifying respiratory variation with force sensor measurements . in 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'11 . IEEE , pp. 3812 - 3815 , Annual International Conference of the IEEE Engineering in Medicine and Biology Society , Boston, MA , United States , 30/08/2011 . https://doi.org/10.1109/IEMBS.2011.6090773

Title: Quantifying respiratory variation with force sensor measurements
Author: Paalasmaa, Joonas; Leppäkorpi, Lasse; Partinen, Markku
Contributor: University of Helsinki, Department of Computer Science
University of Helsinki, Clinicum
Publisher: IEEE
Date: 2011
Language: eng
Number of pages: 4
Belongs to series: 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'11
URI: http://hdl.handle.net/10138/39230
Abstract: Measuring the variation of the respiratory rate makes it possible to analyze the structure of sleep. The variation is high when awake or in REM sleep, and decreases in deep sleep. With sleep apnea, the respiratory variation is disturbed. We present a novel method for extracting respiratory rate variation from indirect measurements of respiration. The method is particularly suitable for force sensor signals, because, in addition to the respiratory phenomenon, they typically contain also other disturbing features, which makes the accurate detection of the respiratory rate difficult. Respiratory variation is calculated by low-pass filtering a force sensor signal at different cut-off frequencies and, at every time instant, selecting one of them for the determination of respiration cycles. The method was validated with a single-night reference recording, which showed that the proposed method detects the respiratory variation accurately. Of the 3421 calculated respiration cycle lengths, 95.9% were closer than 0.5 seconds to the reference.
Subject: 113 Computer and information sciences
217 Medical engineering
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