PPG Signal Classification For Shift Workers Based on Improved ResNet-18

Biological clock disorders can cause a variety of negative effects on the human body's body and psychology, such as sleep, cardiovascular problems, immune system damage, etc. Workers who often work night shifts in factories often face the problem of biological clock disorders. As a bioelectrical signal of the human body, pulse contains a large amount of body information and can effectively reflect physical health. This paper collects the pulse data of 20 day shift workers and night shift workers, uses a variety of network models to train and predict the pulse of the two types of workers, and implements a network model to predict the biological clock and physical health status.The results show that the improved ResNet-18 has the best prediction effect and the accuracy reaches 81.67%.