Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms

Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms

An automated system for sleep spindles detection within EEG background activity, combining two different approaches, is presented. The first approach applies detection criteria on the sigma-band filtered EEG signal, including fuzzy thresholds. The second approach mimics an expert's procedure. A...

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Hauptverfasser: Held, C.M., Causa, L., Estevez, P., Perez, C., Garrido, M., Algarin, C., Peirano, P.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
EEG
Electroencephalography
Electromyography
Electrooculography
Humans
infants sleep
Pathology
Pattern recognition
Pediatrics
Sleep
sleep spindles
Support vector machine classification
Support vector machines
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Zusammenfassung:An automated system for sleep spindles detection within EEG background activity, combining two different approaches, is presented. The first approach applies detection criteria on the sigma-band filtered EEG signal, including fuzzy thresholds. The second approach mimics an expert's procedure. A sleep spindle detection is validated if both approaches agree. The method was applied on a testing set, consisting of continuous sleep recordings of two patients, totaling 1132 epochs (pages). A total of 803 sleep spindles events were marked by the experts. Results showed an 87.7% agreement between the detection system and the medical experts.
DOI:10.1109/IEMBS.2004.1403220