Related Experiment Video
Updated: Mar 17, 2026

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
Published on: November 13, 2019
Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods
Dorothée Coppieters 't Wallant1, Pierre Maquet2, Christophe Phillips1
1GIGA In Silico Medicine, CRC (B30), University of Liège, 4000 Liège, Belgium; Department of Electrical Engineering and Computer Science (B28), 4000 Liège, Belgium; GIGA CRC In Vivo Imaging, CRC (B30), University of Liège, 4000 Liège, Belgium.
Abstract:
Sleep spindle is a peculiar oscillatory brain pattern which has been associated with a number of sleep (isolation from exteroceptive stimuli, memory consolidation) and individual characteristics (intellectual quotient). Oddly enough, the definition of a spindle is both incomplete and restrictive. In consequence, there is no consensus about how to detect spindles. Visual scoring is cumbersome and user dependent. To analyze spindle activity in a more robust way, automatic sleep spindle detection methods are essential. Various algorithms were developed, depending on individual research interest, which hampers direct comparisons and meta-analyses. In this review, sleep spindle is first defined physically and topographically. From this general description, we tentatively extract the main characteristics to be detected and analyzed. A nonexhaustive list of automatic spindle detection methods is provided along with a description of their main processing principles. Finally, we propose a technique to assess the detection methods in a robust and comparable way.
More Related Videos
10:22Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
Published on: December 6, 2016
10:25Multi-system Monitoring for Identification of Seizures, Arrhythmias and Apnea in Conscious Restrained Rabbits
Published on: March 27, 2021