A Method of Sleeping Breathing Signal Recognition

Traditional polysomnography monitoring is complicated and time-consuming, and bracelets and other sleep monitoring devices cannot directly detect respiratory airflow. In this work, we designed a portable sleep monitoring equipment that connects to the forehead and captures data on air flow directly. The sleep monitoring system can gather data from the following modules: blood oxygen, respiration, acceleration sensor, bioelectrical signal collection, and microphone. In addition, this work describes a method for identifying respiratory peak using a dynamic threshold to determine respiratory frequency. Fourteen healthy individuals took part in the investigation, wearing both our portable sleep monitoring equipment and a reference device at night. Due to the obvious phenomenon of baseline drift, the smooth filtering begins after baseline correction. For respiratory events such as oral respiration, apnea, and hypopnea, we set the maximum threshold and minimum threshold update time. The results reveal that the portable sleep monitoring system can accurately identify the breathing peaks.