Heart Rate Characterization as an Initial Sleep Apnea Screening Tool

点击翻译按钮获取中文摘要

Sleep apnea affects between 10-25% of the global adult population and leads to serious ailments such as hypertension, Type II diabetes, and cardiovascular disease. Approximately eight million people in the UK suffer from the condition and this number is growing rapidly. During sleep, cyclic periods in which breathing stops completely followed by a sudden arousal produces a well-defined pattern of alternating low and high heart rates. These episodes of breath cessation during sleep occur less frequently in minor cases of sleep apnea and occur more frequently in severe cases of sleep apnea. In order to diagnose the presence of sleep apnea and quantify the severity, patients must be referred for an overnight study to a sleep lab in a hospital or clinic. Sleep lab testing is inconvenient for the patient and costly for the health-care system and sleep study results require a timely review by a well-trained physician. Furthermore, the sleep study method of sleep apnea detection used currently makes it nearly impossible to track long-term changes in apnea episode count.A new system needs to be developed that can enable ongoing sleep apnea episode tracking to either screen for increasing episode count in individuals at higher risk for developing sleep apnea or to be used as a biomarker that can be used to optimize treatment regimes in those patients that already have a sleep apnea diagnosis. Most people with sleep apnea are unaware that they suffer from the disorder. Providing the general public with an affordable and practical method for sleep apnea screening could potentially be a game-changer in the strive towards a more preventative approach to healthcare.Our goal at Brainstem Digital Health is to develop a wristband wearable device combined with a smartphone application for the remote frequent screening of sleep apnea-related cyclic heart rate patterns. The device will possess high quality medical grade optical sensors for the detection of the pulse wave while the app will provide the user with visual representation of the recent recording as well as long-term data trends. Information regarding total time spent in cyclic heart rate pattern, total number of episodes, and number of episodes per hour will be presented to the user. A sleep hypnogram will also be presented that will demonstrate the association of the apnea-related cyclic heart rate episodes with deep and REM sleep stages.