Multi-physiological signal multi-model interaction-based high-speed railway dispatcher stress detecting method

Abstract

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.

Description

technical field [0001] The invention relates to a stress detection method based on EEG, ECG and eye movement, in particular to a high-speed rail dispatcher stress detection method based on multi-physiological signal multi-model interaction. Background technique [0002] Over the years, after the construction of new high-speed railway lines and the high-speed transformation of existing railways, my country already has the world's largest high-speed railway network with the highest operating speed. High-speed trains run at high speed and density. Once an accident occurs, the result will be disastrous. Therefore, the absolute safety of high-speed railway operation must be guaranteed. This requires the dispatcher to be able to grasp the running status of the train and the status of various driving equipment in real time, receive all kinds of information that endangers driving safety in a timely manner, and make correct judgments and decisions, so as to effectively deal with vari...

AI Technical Summary

Problems solved by technology

However, because people often make wrong judgments and decisions in a state of stress, the so-called stress refers to the highly tense emotional state caused by unexpected urgent and dangerous situations, so the dispatcher made in the state of stress There may be potential safety hazards in dispatching. Based on this situation, the present invention relates to a stress detection method for high-speed rail dispatchers based on multi-physiological signal and multi-model interaction. Through this method, it is possible to effectively detect whether the high-speed rail dispatcher is working in a stressful state , so as to effectively prevent the dispatcher from making wrong judgments and decisions under stress

[0003] Most of the current research focuses on one physiological signal, but due to the complexity of tasks in real work, the measurement of stress response by any single physiological indicator is one-sided, and only the comprehensive use of multiple physiological indicators can accurately detect stress. reaction

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