Fatigue monitoring system and method fusing myoelectricity and electrocardiosignals

Abstract

The invention discloses a fatigue monitoring system and method fusing myoelectricity and electrocardiosignals. The system comprises a surface electromyogram signal electrode module, a surface electromyogram signal acquisition and conversion module, a surface electromyogram signal data processing module, an electrocardiosignal acquisition and conversion module, an electrocardiosignal data processing module and a nonlinear support vector machine algorithm data fusion module. The method comprises the steps that firstly, driver surface electromyogram signals are collected, then signal amplification, filtering and A / D conversion are carried out, and then analysis is carried out to obtain characteristic parameters of the driver surface electromyogram signals; then, electrocardiosignals of a driver are collected, amplification, filtering and A / D conversion are carried out, and then characteristic parameters of the electrocardiosignals of the driver are obtained through analysis; and feature layer fusion is performed on the surface electromyographic signal feature parameters and the electrocardiographic signal feature parameters of the driver to obtain a fatigue feature vector, and the fatigue condition of the driver is judged by judging whether the feature vector conforms to fatigue features or not. The risk of fatigue driving of the driver is reduced.

Description

technical field [0001] The invention belongs to the technical field of biomedical electronics, and in particular relates to a fatigue monitoring system and method. Background technique [0002] With the development of the economy and the improvement of the quality of life of the people, the transportation industry is booming. Many newcomers are involved in the transportation industry, but their daily work and rest are not regular. When driving for a long time, the driver will inevitably get stuck sometimes, and a momentary negligence may lead to traffic accidents. Analysis of current traffic accidents shows that 75% of traffic accidents are attributed to human factors, and 21% of traffic accidents are due to fatigue driving. The dangers of fatigue driving are obvious, and the importance of how to prevent fatigue driving is self-evident. Therefore, more and more attention has been paid to the fatigue monitoring system using EMG or ECG signals. Invention patent 201610264968...

AI Technical Summary

Problems solved by technology

Invention patent 201610264968.4 discloses a fatigue detection system and method based on video intelligent algorithm. The detection of the system includes judging whether the staff is on duty, judging the opening and closing of the staff's eyes and mouth, but the fusion method uses a simple weighted average calculation. In the field of traffic driving where the environment and human behavior change, it is difficult to accurately perform high-precision detection

Invention patent 201521125712.2 discloses a driver fatigue detection system based on surface electromyography technology. The fatigue detection terminal device is designed as a wearable headband. The wearable headband includes a start / stop button, surface electromyography detection electrodes, data processing and Controllers, vibration motors and wireless transmitters, but a single bioelectric signal obviously cannot meet the requirements of high-precision and error-free detection of variable fatigue information

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