.png){kind=icon}
.png){kind=icon}
Return
Individual K-complex localization with multi-scale learning framework in sleep electroencephalography
.png){kind=icon}
PRE
AI
DOI：10.1016/j.bspc.2026.110418.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Accurate detection of K-complex events in sleep electroencephalography (EEG), particularly with respect to their precise onsets and durations, is critical for research on sleep processes and clinical applications. However, the automated localization of K-complexes has long faced performance bottlenecks due to the significant individuality in their morphology across different subjects.
Keywords:
K-complex
sleep electroencephalography
automated localization
multi-scale learning
individual variability
Journal
IF:
4.9
Papers:
9.8K
Citations:
2.4W