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|Title:||Characterizing respiratory waveform regularity and associated thoraco-abdominal asynchrony during sleep using respiratory inductive plethysmography|
|Citation:||2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 2-5 April 2013, Melbourne, Australia / M. Palaniswami C. Leckie S. Kanhere J. Gubbi (eds.): pp.329-332|
|Conference Name:||International Conference on Intelligent Sensors, Sensor Networks and Information Processing (8th : 2013 : Melbourne, Australia)|
|Sarah A. Immanuel, Yvonne Pamula, Mark Kohler, David A. Saint, Mathias Baumert|
|Abstract:||Assessment of breathing in polysomnographic studies is commonly performed by measuring ribcage and abdominal movements using respiratory inductive plethysmographic (RIP) effort sensors, in addition to nasal/oral airflow measurements. This paper aims to analyse RIP signals in healthy children for the degree of respiratory regularity across sleep stages. We quantified (a) respiratory waveform regularity by computing the percentage of low frequency energy (%LFE) using a wavelet-based approach and (b) associated thoraco-abdominal asynchrony (TAA) by computing the phase deviation between the ribcage and abdominal signals using a Hilbert transform approach, and examined the influence of sleep stages on these measures. Five minute segments of quiet breathing data during stage 2, 4 non-rapid eye movement (NREM) sleep and rapid-eye-movement (REM) sleep were extracted. The %LFE contained in the frequency range of 0.02 to 0.05 Hz was computed from the ribcage signal and TAA was calculated between corresponding ribcage and abdominal excursions. Sleep stage effects were significant for both measures with REM sleep exhibiting the greatest respiratory waveform irregularity and asynchrony compared to NREM sleep stages 2 and 4. Also TAA and %LFE were significantly correlated in REM sleep [r=0.625 p<;0.01], suggesting that the lower the coordination between ribcage and abdominal compartments, the larger the respiratory waveform irregularities. To conclude, the proposed non-invasive asynchrony and regularity analysis of RIP breathing signals provides insight into respiratory mechanics during sleep in normal healthy children.|
|Rights:||© 2013 IEEE|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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