2017 · 17 citations · 16 references
Life SciencesPhysiologyBiomedical Signal ProcessingSensor FusionSleep MedicineCardiovascular MonitoringSleep PhysiologySleep Signal AnalysisVital SignsVital Signs AssessmentVital Signs RecordingGround Truth LabelingHeart RateOxygen SaturationPhotoplethysmogram Signal ProcessingPulse OximetrySleep Apnea DetectionSleep Apnea DiagnosisSleep Apnea Monitoring
This paper presents a study on identifying sleep apnoea using the photoplethysmography (PPG) measurements, which is obtained from the SpO2 sensor. Using a database of polysomnogram (PSG) records of 52 patients, the heart rate and breathing effort information was derived from the PPG measurements and then features are extracted and processed by a classifier to detect one-minute epochs of sleep apnoea. The ground truth labels for the epochs were determined by trained technicians using the full PSG signal. Pulse oximetry (SpO2) measurements from the same sensor are also used in the classification process for comparison and in combination with the PPG results. The results show that both the heart rate and respiratory effort information derived from the PPG signal were able to detect apnoeic epochs with some success. The best classification performance of 87% for correctly labelling the epochs was obtained when the SpO2 features and the PPG features were combined.
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Jesús Lázaro, Eduardo Gil, José María Vergara et al. · IEEE Journal of Biomedical and Health Informatics · 2013 · 151 citations