Olfaction electroencephalogram and random forest-based method for classifying sensory substances
A random forest and brain wave technology, applied in sensors, medical science, diagnostic recording/measurement, etc., can solve problems such as poor repeatability, doping with subjective factors, and inability to fully reflect the real feeling of the human body, and achieve a simple and rigorous sensory evaluation process Sexuality and scientificity, the effect of reducing costs
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[0021] Materials and methods: 3 different brands of beer (Tsingtao, Cordon Bleu, Harbin) were selected, and their alcohol concentrations and raw materials are shown in Table 1 below:
[0022] Table 1 Samples of 3 different brands of beer
[0023]
[0024] In terms of olfactory EEG signal analysis, the EEG signals used are self-collected data in the laboratory. After the original EEG signals are collected, EEG preprocessing is performed first (including deleting bad areas, filtering out 50Hz power frequency interference, and superimposing data. average, wavelet transform and other steps); Considering that the collected electrodes contain different regions, the electrode screening is carried out; then it is linearly analyzed, and the peak value, mean value, variance, center frequency, maximum power and The power sum is used as the feature value; finally, the selected feature value is sent to the corresponding classifier to obtain the final classification accuracy. The data p...
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