Clinical-level screening of sleep apnea syndrome with single-lead ECG alone is achievable using machine learning with appropriate time windows.

Journal: Sleep & breathing = Schlaf & Atmung
PMID: 40214940

Abstract

PURPOSE: To establish a simple and noninvasive screening test for sleep apnea (SA) that imposes less burden on potential patients. The specific objective of this study was to verify the effectiveness of past and future single-lead electrocardiogram (ECG) data from SA occurrence sites in improving the estimation accuracy of SA and sleep apnea syndrome (SAS) using machine learning.

Authors

  • Takahiro Yamane
    Department of Biomedical Informatics, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.
  • Masanori Fujii
    Department of Geriatric Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
  • Mizuki Morita
    Okayama University, Okayama, Japan.

Keywords

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