Abstract

Quantitative analysis of sleep EEG data can provide valuable additional information in sleep research. However, analysis of data contaminated by artifacts can lead to spurious results. Thus, the first step in realizing an automatic sleep analysis system is the implementation of a reliable and valid artifact processing strategy. This strategy should include: (1) high-quality recording techniques in order to minimize the occurrence of avoidable artifacts (e.g. technical artifacts); (2) artifact minimization procedures in order to minimize the loss of data by estimating the contribution of different artifacts in the EEG recordings, thus allowing the calculation of the ‘corrected’ EEG (e.g. ocular and ECG interference), and finally (3) artifact identification procedures in order to define epochs contaminated by remaining artifacts (e.g. movement and muscle artifacts). Therefore, after a short description of the types of artifacts in the sleep EEG and some typical examples obtained in different sleep stages, artifact minimization and identification procedures will be reviewed.

Keywords

Artifact (error)ElectroencephalographyComputer scienceSpurious relationshipIdentification (biology)Sleep StagesArtificial intelligenceSleep (system call)Pattern recognition (psychology)Speech recognitionPolysomnographyMachine learningPsychologyNeuroscience

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Publication Info

Year
1999
Type
review
Volume
40
Issue
3
Pages
150-157
Citations
162
Access
Closed

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P. Anderer, Stephen Roberts, Alois Schlögl et al. (1999). Artifact Processing in Computerized Analysis of Sleep EEG – A Review. Neuropsychobiology , 40 (3) , 150-157. https://doi.org/10.1159/000026613

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DOI
10.1159/000026613