The invention relates to a multi-physiological signal multi-model interaction-based high-speed railway dispatcher stress detecting method. An electroencephalogram signal collecting device, a cardiograph collecting device and an eye movement collecting device are adopted to acquire corresponding physiological signals in a linkage way to be subjected to information collection, so that the stress states of high-speed railway dispatchers are judged; after characteristic selection, model training and information fusion processing, electroencephalogram, cardiograph and eye movement identification results which are analyzed on the basis of three models, i.e. a BP (Back Propagation) neural network model, a SVM (Support Vector Machine) model and an HMM (Hidden Markov Model) markov model, are subjected to information fusion, and better electroencephalogram, cardiograph and eye movement identification results are extracted; the electroencephalogram, cardiograph and eye movement identification results are fused again, and finally a fusion characteristic identification result is obtained to quickly judge the stress states of the high-speed railway dispatchers.
Multi-physiological signal multi-model interaction-based high-speed railway dispatcher stress detecting method