Equipment Test Personnel Fatigue Detection Based on Particle Swarm Optimization and Support Vector Machine

This paper addresses the safety risks posed to equipment testers who operate under physically and mentally demanding conditions in harsh field environments, which can lead to excessive fatigue. It examines the fatigue characteristics of equipment operators, identifies physiological parameters indicative of fatigue, and constructs a fatigue detection model using the Support Vector Machine (SVM) method. This model is further optimized with Particle Swarm Optimization (PSO) algorithms, and its effectiveness and accuracy are validated through empirical examples.