Ergonomic Reliability Assessment of VDT System for Operation Design Based on Improved BPNN and HCR under Special Circumstances

Ergonomic reliability plays a significant role in the safe operation of devices. With spread infectious diseases around world, work environments with high loads and infection rates, medical staff state self-protection. The use visual display terminal (VDT) for equipment has undergone fundamental changes, traditional human-machine interface design needs to be improved. After completion development, VDT enters experimental testing stage, which limitations simulating high-load high-infection environments. cost is high, subjects face harsh conditions; thus, an ergonomic model that can predict such special circumstances must established. An based on improved backpropagation neural network (BPNN) human cognition (HCR) proposed predicting evaluating flows according VDTs. Firstly, small data sample used train BPNN generate ensure suitable accuracy. To prevent from falling into local optimal solutions, bat algorithm introduced improve BPNN. Compared BPNN, superiority clearly demonstrated. Secondly, HCR method analyze highlight changes factor VDTs different time processes operating prediction results, provide reference selecting method. Finally, validity availability are verified through eye tracker experiment statistical analysis results.