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Joint symbolic dynamics as an effective approach for quantification of cardio-respiratory interaction in patients with obstructive sleep apnea syndrome

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5 Author(s)
Muammar M. Kabir ; Centre for Biomedical Engineering, School of Electrical and Electronic Engineering, The University of Adelaide, SA 5005, Australia ; Hany Dimitri ; Prashanthan Sanders ; Derek Abbott
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The aim of this study was to quantify cardiorespiratory interaction in patients with obstructive sleep apnea syndrome (OSAS) during night-time sleep using our recently proposed technique based on joint symbolic dynamics (JSD) and compare it with the synchrogram technique. We investigated overnight polysomnography data of 213 patients with OSAS. The R-R time series were extracted from electrocardiograms (ECG) and respiratory phases were obtained from abdominal displacement sensors using the Hilbert transform. For the JSD technique, both series were transformed into ternary symbol vectors based on the changes between two successive R-R intervals and the respective respiratory phases. Subsequently, words of length `3' were formed and the correspondence between words of the two series was determined for each sleep stage to quantify cardio-respiratory interaction. To determine the effect of OSAS severity on cardiorespiratory interaction, the cohort was trichotomized based on the apnea-hypopnea index (AHI): AHI≤15, 15<;AHI<;30, and AHI≥30. Using JSD approach, we found significantly lower cardiorespiratory interaction in patients with moderate and severe OSAS compared to patients with no/mild OSAS (slow-wave sleep: 20.9±4.7 vs. 17.8±3.5 and 15.5±4.7, p<;0.0001, respectively). Compared to the synchrogram technique, the JSD approach appears to be more sensitive and efficient for the analysis of cardio-respiratory interaction in patients with OSAS.

Published in:

Electrical & Computer Engineering (ICECE), 2012 7th International Conference on

Date of Conference:

20-22 Dec. 2012