Enhanced Detection of Sleep Apnoea using Heart-Rate, Respiration Effort and Oxygen Saturation Derived from a Photoplethysmography Sensor

Abstract

This paper presents a study on identifying sleep apnea using the photoplethysmography (PPG) measurements, which is obtained from a low-cost, non-invasive and a convenient-to-use sensor. Using a database of polysomnogram records of 52 patients, the heart rate and breathing effort information is derived from the PPG measurements and then features are extracted and applied to a classification model to detect sleep apnea. The apnea classification is carried out for each one-minute segment of the signal. Pulse oximetry (SpO2) measurements from the same database 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 apneic segments with some success. The best apnea classification performance was obtained when we combined the SpO2 features and the PPG features.