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In this paper, an adaptive neuro-fuzzy inference system (ANFIS) for sleep spindle detection was developed. Two input variables including teager energy operator (TEO) and sigma index analyses of the EEG signals were extracted. 1180 training samples (0.5 s) of 15 subjects were used to ANFIS training, include 397 spindle and 783 non-spindle waveform. Then the 1519 epochs (30s) of other 15 subjects were...
In this paper, we propose an automatic sleep-scoring method combining multiscale entropy (MSE) and autoregressive (AR) models for single-channel EEG and to assess the performance of the method comparatively with manual scoring based on full polysomnograms. This is the first time that MSE has ever been applied to sleep scoring. All-night polysomnograms from 20 healthy individuals were scored using...
In this paper, a rule-based automatic sleep staging method was proposed. Twelve features, including temporal and spectrum analyses of the EEG, EOG, and EMG signals, were utilized. Normalization was applied to each feature to reduce the effect of individual variability. A hierarchical decision tree, with fourteen rules, was constructed for sleep stage classification. Finally, a smoothing process considering...
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