Non-contact Human Fatigue Assessment System Based on Millimeter Wave Radar

In order to measure the heart rate and breath rate of human-body and evaluate the fatigue level in real-time, a noncontact human fatigue assessment system based on millimeter wave radar AWR1642 is proposed in this paper to assess the health condition of human conveniently. It has the characteristics of high classification accuracy and high accuracy. The function of system mainly includes getting accurate heart rate and breath rate by AWR1642, establishing data set, extracting features, annotating data and predicting fatigue level by Particle Swarm optimization Back Propagation (PSO-BP) neural network model. The experiment results show that, heart rate got by AWR1642 had an error less than 5% compared with heart rate got by standard medical oximeter. The system can be used for the parameters measurement of vital sign. On the other hand, the PSO-BP neural network model built with the variance of heart rate and breath rate is difficult to cause over fitting. The system has a good practicability can be used for the prediction of fatigue level and it's accuracy can reach 93.74%.