Poor and monotonous work could easily lead to a decrease of arousal level of the monitoring work personnel. In order to improve the performance of monitoring work, low arousal level needs to be recognized and awakened. We proposed a recognition method of low arousal by the electroencephalogram (EEG) as the object of study to recognize the low arousal level in the vigilance. We used wavelet packet transform to decompose the EEG signal so the EEG rhythms of each component were obtained, and then we calculated the parameters of relative energy and energy ratio of high-low frequency, and constructed the feature vector to monitor low arousal state in the operation. We finally used support vector machine (SVM) to recognize the low arousal state in the simulate operation. The experimental results showed that the method introduced in this article could well distinguish low arousal level from arousal level in the vigilance and it could also get a high recognition rate. Have been compared with other analysis methods, the present method could more effectively recognize low arousal level and provide better technical support for wake-up mechanism of low arousal state.
Arousal ; Brain ; physiology ; Electroencephalography ; Humans ; Signal Processing, Computer-Assisted ; Support Vector Machine ; Wavelet Analysis

To adapt to the system reformation of medical laboratory science from five academic years to four academic years and to meet the new professional technology-oriented requirements, the medical laboratory science institute of Guangdong Medical College has carried out a comprehensive reform of curriculum system. This paper has analyzed the current problems in the school medical ex-amination and explored the curriculum system reform from three respects such as adjusting curriculum by restructuring and integrating programs, implementing modular teaching to build its characteristics and strengthening practice teaching.And it has also explored the full assessment mode by optimizing the traditional one-stop assessment.