A snoring classifier based on heart rate variability analysis

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.

Medos relacionados à anestesia e associados ao perfil sociodemográfico de pacientes na consulta pré-anestésica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

O dispositivo analítico no hospital na clínica com transexuais: entre o ser e o sujeito

Pós-graduação em Psicologia - FCLAS

A classification of Pepper yellow mosaic virus isolates into pathotypes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)