Sleep Event Detection

Sleep Event Detection is a methodological framework in sleep signal analysis that identifies and classifies specific physiological occurrences, such as apneas, arousals, or limb movements, within polysomnographic or ambulatory sleep recordings by distinguishing them from background activity through signal特征-based pattern recognition.

496

Publications

22.1K

Citations

1.8K

Authors

721

Institutions

Publications per year

2017–2026

225

Authors

1.8K

  1. HB
    Helge B. D. Sørensen

    Technical University of Denmark, Denmark

    9 publications · 632 citations

    10

    h-index

  2. PJ
    Poul Jennum

    University of Copenhagen, Denmark

    8 publications · 616 citations

    10

    h-index

  3. JH
    Jóel Hasan

    8 publications · 279 citations

    8

    h-index

  4. TP
    Thomas Penzel

    Charité - Universitätsmedizin Berlin, Germany

    6 publications · 395 citations

    7

    h-index

  5. EM
    Emmanuel Mignot

    Stanford University, United States

    5 publications · 515 citations

    7

    h-index

1–5 of 1.8K

Venues

  1. IEEE Transactions on Biomedical Engineering

    21 publications · 1.5K citations

    19

    h-index

  2. SLEEP

    16 publications · 1.1K citations

    16

    h-index

  3. Journal of Neuroscience Methods

    12 publications · 889 citations

    12

    h-index

  4. Journal of Sleep Research

    JSR · 11 publications · 535 citations

    11

    h-index

  5. Computers in Biology and Medicine

    10 publications · 627 citations

    10

    h-index

1–5