Beyond K-complex binary scoring during sleep: probabilistic classification using deep learning.

Journal: Sleep
Published Date: Oct 13, 2020

Abstract

STUDY OBJECTIVES: K-complexes (KCs) are a recognized electroencephalography marker of sensory processing and a defining feature of sleep stage 2. KC frequency and morphology may also be reflective of sleep quality, aging, and a range of sleep and sensory processing deficits. However, manual scoring of K-complexes is impractical, time-consuming, and thus costly and currently not well-standardized. Although automated KC detection methods have been developed, performance and uptake remain limited.

Authors

  • Bastien Lechat
    Adelaide Institute for Sleep Health, College of Science and Engineering, Flinders University, Adelaide, Australia.
  • Kristy Hansen
    Adelaide Institute for Sleep Health, College of Science and Engineering, Flinders University, Adelaide, Australia.
  • Peter Catcheside
    Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, Australia.
  • Branko Zajamsek
    Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, Australia.

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