Coupling analysis of heart rate variability and cortical arousal using a deep learning algorithm

• Published in: PloS one Vol. 18; no. 4; p. e0284167
• Main Authors: Huo, Jiayan, Quan, Stuart F., Roveda, Janet, Li, Ao
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 06.04.2023; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Arousal; Arousal - physiology; Arteriosclerosis; Atherosclerosis; Autonomic nervous system; Autonomic Nervous System - physiology; Biology and Life Sciences; Computer and Information Sciences; Cortical maps; Data mining; Datasets; Deep Learning; Development and progression; Diagnosis; EKG; Electrocardiogram; Electrocardiography; Electroencephalography; Etiology; Evaluation; Eye movements; Female; Heart; Heart beat; Heart rate; Heart Rate - physiology; Humans; Machine learning; Medicine and Health Sciences; Nervous system; Neural networks; Physical Sciences; Population studies; Probability; Research and Analysis Methods; Risk factors; Segments; Sleep; Sleep - physiology; Sleep apnea; Sleep disorders; Sympathetic nervous system; Time domain analysis; Variability; United States
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0284167

Frequent cortical arousal is associated with cardiovascular dysfunction among people with sleep-disordered breathing. Changes in heart rate variability (HRV) can represent pathological conditions associated with autonomic nervous system dysfunction. Previous studies showed changes in cardiac activity due to cortical arousals. However, few studies have examined the instantaneous association between cortical arousal and HRV in an ethnically diverse population. In this study, we included 1,069 subjects’ full night ECG signals from unattended polysomnography in the Multi-Ethnic Study of Atherosclerosis dataset. An automated deep learning tool was employed to annotate arousal events from ECG signals. The etiology (e.g., respiratory, or spontaneous) of each arousal event was classified through a temporal analysis. Time domain HRVs and mean heart rate were calculated on pre-, intra-, and post-arousal segments of a 25-s period for each arousal event. We observed that heart rate and HRVs increased during the arousal onsets in the intra-arousal segments, regardless of arousal etiology. Furthermore, HRVs response to cortical arousal occurrence differed according to gender and the sleep stages in which arousal occurred. The more intense HRVs variation due to arousal in females can contribute to a potentially stronger association between arousal burden and long-term mortality. The excessive abrupt sympathetic tone elevation in REM caused by arousal may provide insights on the association between sleep and sudden cardiac death.