Signal processing based on wavelet change and random forest
In order to accurately and effectively evaluate the mental health status of college students,the study collected the bio-logical signal data by using the mental acquisition device,and processed and analyzed the signal by using the wavelet transform and random forest method.The mental signal processing method was verified and found that the classification evaluation error of anxiety and depression was 6.7%and the running time was 2.7 s,so the evaluation performance and efficiency were better than other meth-ods.Therefore,the study used this method to evaluate the psychological status of a college student,and found that the proportion of anxiety,depression,anxiety and depression was 3.5%,4.5%and 3.5%,which were higher than that of other grades.In conclu-sion,the results show that senior students'psychological pressure is greater,and university educational institutions should strengthen the mental health support and care for senior students,and help students improve their ability to cope with stress and emotional man-agement.
college studentsmental acquisition devicewavelet transformrandom forestsignal processing