The conventional approach to monitoring sleep stages requires placing multiple sensors on the patients, which is inconvenient for long-term monitoring and requires expert support. We propose a single sensor Photoplethysmographic (PPG) based automated multi-stage sleep classification. This experimental study recorded the PPG during the entire night's sleep of ten patients. Data analysis was performed to obtain 82 features from the recordings, which were then classified against the sleep stages. The classification results using SVM with the polynomial kernel gave the overall accuracy of 84.66%, 79.62%, and 72.23% for two, three, and four-stage sleep classification. These results show that using only PPG; it is possible to conduct sleep stage monitoring. These findings open the opportunities for PPG-based wearable solutions for home-based automated sleep monitoring.

The PSG data were recorded for the night sleep duration of ten participants (9 male/ 1 female, age 43–75 years). The length of sleep time ranged from 6.8 to 10.1 hours. All participants were volunteers and recruited from the out-patients at Charite Hospital, Berlin, Germany. All suffered sleep-disordered breathing and were free from a history of cardiac issues. The diagnosis was based on PSG outcomes and clinical symptoms. The research and data collection protocol was approved by the Charite Hospital Committee for Ethics in Human Research (2018), Berlin, Germany, and the experiments were conducted in accordance with the Helsinki declaration for ethical experiments, revised in 2013. Written consent was taken prior to the experiments. The demographic information of the subjects. Each PSG recording included two-channel EEG (channel C3-A2 and C4-A1), ECG, PPG, left and right EOG, leg movements, thoracic and abdominal wall expansion, arterial oxygen saturation SaO2, and oronasal airflow. According to the American Academy of Sleep Medicine (AASM) criteria, the PSG recordings were segmented into 30-second epochs, and an expert sleep physiologist labelled sleep stages.

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