Actas de congresos
A snoring classifier based on heart rate variability analysis
Fecha
2011-12-01Registro en:
Computing in Cardiology, v. 38, p. 345-348.
2325-8861
2325-887X
2-s2.0-84859963132
Autor
University of Macau
Technical University of Lisbon
Universidade Estadual Paulista (Unesp)
Institución
Resumen
The effect of snoring on the cardiovascular system is not well-known. In this study we analyzed the Heart Rate Variability (HRV) differences between light and heavy snorers. The experiments are done on the full-whole-night polysomnography (PSG) with ECG and audio channels from patient group (heavy snorer) and control group (light snorer), which are gender- and age-paired, totally 30 subjects. A feature Snoring Density (SND) of audio signal as classification criterion and HRV features are computed. Mann-Whitney statistical test and Support Vector Machine (SVM) classification are done to see the correlation. The result of this study shows that snoring has close impact on the HRV features. This result can provide a deeper insight into the physiological understand of snoring. © 2011 CCAL.