A Study for ERP Classification of Food Preference Based on CSP and SVM
Li Chunyu1, He Feng2*, Qi Hongzhi2, Guo Xiaoyi1, Chen Long1, Ming Dong1
1(Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China) 2(School of Precision Instruments and Opto-electronics Engineering, Tianjin University, Tianjin 300072, China)
Abstract：In this study an ERP experiment was conducted to investigate the difference of ERP evoked by individual food preferences. A new classification method was proposed. The oddball paradigm was adopted and 18 subjects participated in this experiment. After ranking 5 kinds of food, ERP was induced by different food stimulus, and the highest and lowest score were collected. The ERPs were analyzed to determine whether there were significant differences in the signals related to the different food. Next, common spatial pattern and support vector machines were used for feature extraction and single-trial ERP classification respectively. The leave-one-out method was used for cross validation. Results showed that P3 amplitudes for food with high or low score were different significantly and P3 amplitudes were larger in the former compared to the latter. The average amplitude increased by about 15%. A positive correlation between P3 amplitudes and food scores was seen. The averaged accuracy of classification could reach 93.16% when 4 single-trial ERP were used. These results suggested that brain reactivities responding to food preferences were quite different and the proposed method achieved expected results. In conclusion, ERP can be used as a new tool for food preference analysis and provides a new solution to food evaluation and assistant treatment about anorexia.
李春雨, 何峰, 綦宏志, 郭晓艺, 陈龙, 明东. 基于共空间模式和支持向量机算法的食物偏好脑电分类研究[J]. 中国生物医学工程学报, 2022, 41(3): 266-272.
Li Chunyu, He Feng, Qi Hongzhi, Guo Xiaoyi, Chen Long, Ming Dong. A Study for ERP Classification of Food Preference Based on CSP and SVM. Chinese Journal of Biomedical Engineering, 2022, 41(3): 266-272.
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