An automatic interpretation system for an awake background EEG has been developed by the authors, and gave satisfactory results. The detection of EEG components (dominant rhythm and slow wave) is important in this system. However, it is difficult to detect the EEG component, which appears in short time, because the EEG component is detected based on the power spectrum for the EEG data of 5 sec in this system. In this study, a method for detecting the dominant rhythm and the slow wave with short duration by using AR (auto-regressive) model is proposed. First, AR models are constructed for the EEG data of short period, and peak frequency and power of main component in short period are calculated from the poles of AR models. The dominant rhythm and the slow wave are detected by using these parameters. The proposed method was applied for EEG data, and brought satisfactory results. Furthermore, the proposed method can judge the “organization of dominant rhythm” and “rhythmicity of slow wave”. By introducing the proposed method in the automatic EEG interpretation system, this system becomes more powerful for assisting the electroencephalographer for their EEG interpretation.

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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[in Japanese]

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