Abstract
The cyclic alternating pattern is the periodic electroencephalogram activity occurring during non-rapid eye movement sleep. It is a marker of sleep instability and is correlated with several sleep-related pathologies. Considering the connection between the human heart and brain, our study explores the feasibility of using cardiopulmonary features to automatically detect the cyclic alternating pattern of sleep and hence diagnose sleep-related pathologies. By statistically analyzing and comparing the cardiopulmonary characteristics of a healthy group and groups with sleep-related diseases, an automatic recognition scheme of the cyclic alternating pattern is proposed based on the cardiopulmonary resonance indices. Using the Hidden Markov and Random Forest, the scheme combines the variation and stability of measurements of the coupling state of the cardiopulmonary system during sleep. In this research, the F1 score of the sleep-wake classification reaches 92.0%. In terms of the cyclic alternating pattern, the average recognition rate of A-phase reaches 84.7% on the CAP Sleep Database of 108 cases of people. The F1 score of disease diagnosis is 87.8% for insomnia and 90.0% for narcolepsy.
Highlights
IntroductionAcademic Editors: Feng Hong, Sleep, which accounts for nearly a third of human life, is an important function that helps the body to recover
Quiet sleep is associated with increased parasympathetic arousal and activity, while rapid eye movement (REM) sleep is relevant to the increased sympathetic activity [6]
This section describes the statistical analysis of the cardiopulmonary characteristics of people with non-pathology and several sleep-related pathologies
Summary
Academic Editors: Feng Hong, Sleep, which accounts for nearly a third of human life, is an important function that helps the body to recover. It has been proven that sleep could help to reduce stress, regulate hormone balance, stabilize appetite and cardiovascular function [1–3]. Sleep is essential for the recovery of the brain function, which is closely related to brain development, learning, memory and mental health of human beings [4]. The monitoring of sleep and the detection of sleep-related diseases are of great significance in people’s daily life as well as in clinical treatment. The sleep structure is based on the cyclical alternation of two main neurophysiological states: REM and NON-REM (NREM) sleep [7]. The alternations of non-REM and REM sleep constitute the sleep cycle, and its recurrence during the night determines the classical progressive sleep mode
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
