Research on Fatigue Detection Method of Equipment Operators Based on Multi-Source Physiological Signals

Abstract

In order to effectively detect the fatigue status of equipment operators, this paper proposes a fatigue detection model that integrates multi-source physiological signals to evaluate the fatigue level of equipment operators in order to improve the efficiency of military operations and training. This method selects various physiological signals such as human heart rate, heart rate variability, body temperature, respiratory rate, blood oxygen concentration, etc. according to the working environment and working characteristics of the equipment operator, and establishes the relationship between the characteristic values of various physiological parameters and fatigue levels, And then use the optimized support vector machine to perform fusion judgment on the feature values of multi-source physiological parameters, and obtain the fatigue state of the equipment operator. Experimental results show that this method can make a more accurate judgment on the fatigue state of equipment operators, and is of great significance for ensuring the efficiency of equipment operators’ work and training.