Abstract

GUERRERO-MORA, G. et al. Multichannel Analysis of an Unobtrusive Sensor for Sleep Apnea-Hypopnea Detection. Rev. mex. ing. bioméd [online]. 2014, vol.35, n.1, pp.29-40. ISSN 2395-9126.

This manuscript presents an unobtrusive method for sleep apneahypopnea syndrome (SAHS) detection. The airflow is indirectly measured through a sensitive mattress (Pressure Bed sensor, PBS) that incorporates multiple pressure sensors into a bed mattress. The instantaneous amplitude of each sensor signal is calculated through Hilbert transform, and then, the information is reduced via principal component analysis. The respiratory events (ERs -apneas/hypopneas) are detected as a reduction in the resulting instantaneous amplitude and accounted in the respiratory event index (IER), which is a severity indicator similar to the offcial apnea-hypopnea index (AHI). The respiratory signals extracted from PBS are analyzed first by clustering the information coming from channel pairs, and then using the eight channels. The IER performance is compared with the AHI for different severity categories. For the diagnosis of healthy and pathological patients we obtain a sensitivity, specificity and accuracy of 92%, 100% and 96%, respectively using two or eight PBS channels. These results suggest the possibility to propose PBS as an alternative tool for SAHS diagnosis in home environment.

Keywords : Sleep apnea-hypopnea syndrome (SAHS); sensitive mattress (PBS); automatic detection; principal component analysis (PCA); respiratory events.

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )