This article critically reviews 8 computer implementations of Fujimori's method for EEG waveform recognition, with methodological considerations for the application of this method to the analysis of all-night sleep EEG. Fujimori's method has been considered one of the most appropriate waveform analyses for EEG. This kind of analysis is advantageous for measuring frequency and amplitude of each EEG wave separately. However, current implementations have drawbacks which must be resolved before they can be used on all-night sleep EEG. An optimal sampling rate should be determined which is appropriate to the purpose of analysis. Amplitude thresholds for wave recognition, which are now set arbitrarily, should also be improved. Measurement of waves in higher orders of superimposition is also necessary, although existing systems are limited to the second order. Additional algorithms, such as for the separate detection of sleep slow waves, may be useful. Further applications for Fujimori's method are suggested.
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