Combination of AI components for biosignal processing application to sleep stage recognition

Author

Schwaibold, M.H. ; Penzel, T. ; Schochlin, J. ; Bolz, A.

Author_Institution

Med. Inf. Technol., Forschungszentrum Informatik, Karlsruhe, Germany

Volume

2

fYear

2001

fDate

2001

Firstpage

1692

Abstract

We present a novel approach to combining artificial intelligence components for biomedical signal processing. The modular algorithm mimics the step-by-step type procedure of a human expert and includes the two assessment steps most important for sleep stage scoring, pattern recognition in electrophysiological signal channels and rule evaluation for classifying the current sequence of patterns. The application of sleep stage scoring is a complex task in medical informatics. The AR-TISANA (artificial intelligence in sleep analysis) algorithm we have developed provides high rates of correspondence with the results produced by human experts. Additional features are the transparent decision-making process and information about the detailed structure of sleep. This has been achieved by utilizing neural networks for pattern recognition and neuro-fuzzy systems for rule evaluation. The AI components chosen to perform these two classification steps were particularly successful due to their individual strengths.

Keywords

electroencephalography; electromyography; fuzzy neural nets; learning (artificial intelligence); medical expert systems; medical signal processing; multilayer perceptrons; pattern classification; signal classification; sleep; ARTISANA algorithm; EEG; EMG; EOG; K complexes; REM sleep; automatically assessed hypnogram; biomedical signal processing; combined artificial intelligence components; current sequence of patterns; electrophysiological signal channels; modular algorithm; multilayer-perceptron; neural networks; neuro-fuzzy systems; pattern recognition; rule evaluation; self-learning systems; sleep spindles; sleep stage recognition; supervised learning; transient patterns; transparent decision-making process; vertex sharp waves; Algorithm design and analysis; Artificial intelligence; Artificial neural networks; Biomedical informatics; Biomedical signal processing; Decision making; Humans; Pattern recognition; Signal processing algorithms; Sleep;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1020541

Filename

1020541