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Algorithm for automatic detection of self-similarity and prediction of residual central respiratory events during CPAP
2020
Sleep
Study objectives Sleep disordered breathing is a significant risk factor for cardiometabolic and neurodegenerative diseases. High loop gain is a driving mechanism of central sleep apnea or periodic breathing. This study presents a computational approach that identifies "expressed/manifest" high loop gain via a cyclical self-similarity feature in effort-based respiration signals. Methods Working under the assumption that high loop gain increases the risk of residual central respiratory events
doi:10.1093/sleep/zsaa215
pmid:33057718
pmcid:PMC8631077
fatcat:zs54sj5cvzcp5acr2a7zyqgzvu