Spectral properties of the respiratory signal during sleep apnea events: Obtrusive and unobtrusive measurements
Abstract
People with obstructive sleep apnea hypopnea syndrome (OSAHS) are affected by disruption in normal breathing patterns during sleep. In the literature, it is common to find acquisition of Thoracic (THO) and abdominal (ABD) movements with piezo-electric bands included in a full polysomnography. These movements convey valuable information related to sleep apnea events, and for this reason, contactless methods, such as the Pressure Bed Sensor (PBS), have been developed to extract this information. The main goal of this study is to analyze apnea and hypopnea fluctuations based on the spectral analysis of nasal airflow measure (as a reference signal), thoraco–abdominal effort and PBS respiration signal. To this end, features from the respiratory spectrum such as entropy, Gaussian modeling and instantaneous frequency were computed. These spectral properties were evaluated in three windows for each sensor: control point (CP) which is a window randomly extracted for the sleep time without apnea event, before event (BE) a window before an apnea episode and during event (DE) a window during an apnea episode. Apnea and hypopnea events were analyzed separately. According to a database of seventeen subjects, DE windows showed significant differences with respect to the CP window in most of the computed indices for both apnea and hypopnea events for all sensors. Significant differences were also found when DE and BE windows were compared in the case of apnea for all the sensors. In conclusion, the analyzed spectral characteristics could be a good tool to detect apnea and hypopnea. Finally, PBS signal which is a unobtrusive sensor, maintains the spectral properties of the standard respiratory effort measurements, and the use of this sensor could be useful for the monitoring outside of a clinical environment, simplifying the acquisition process.
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