Attention Level Evaluation Based on Physiological Signals and Support Vector Machine

摘要

The The phenomenon of low attention level has become a serious problem and may generate negative influences in some occasions. Thefore, it is significant to find a method for detecting and making an improve of the low attention level. In this paper, we try to investigate the relationship between physiological signals and attention level. Performance data generated by the subjects were used to dertermine levels of attention. EEG and EGG signals under different attention levels were compared, and some changes like EEG sub-band power and ECG RR-intervals were found. Then, Support Vector Machines were used to make a classfication between differnent attention levels. It would be used to detect the attention level through the physiological signals and help to sustain an optimal attention level.