Fatigue state monitoring and early warning method and system thereof
A fatigue state and monitoring module technology, applied in the field of fatigue detection, can solve the problems of slow discrimination and low accuracy, and achieve the effects of high safety, improved reliability, and improved speed and accuracy
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Embodiment 1
[0047] This embodiment provides a fatigue state monitoring and early warning method, including the following steps:
[0048] (1) Preset a fatigue state monitoring and early warning system, which includes a physiological information collection module, a wireless communication module and a monitoring module, wherein the physiological information collection module has a built-in dry state electrode sensor and an intelligent chip, and the monitoring module includes mutual A connected main control unit and an early warning unit, the main control unit includes a preprocessing subunit, a model building subunit and a fusion subunit;
[0049] (2) Regularly collect the electroencephalogram signal of the person under test through the physiological information collection module, the dry electrode sensor in the physiological information collection module collects the bioelectrical signal generated by the brain, and sends the collected bioelectrical signal into the In the smart chip, the sm...
Embodiment 2
[0057] see Image 6 and Figure 7 The main difference between this embodiment and Embodiment 1 is that: the main control unit in the step (1) also includes a feature extraction subunit and a fusion subunit; the step (2) also includes: the physiological information collection module The human eye image signal of the person under test is regularly collected; the step (3) also includes: the wireless communication module transmits the human eye image signal to the monitoring module; the step (4) also includes: the preprocessing subunit Preprocessing the human eye image signal, the preprocessing includes denoising, grayscale and equalization processing on the human eye image signal data; the feature extraction subunit extracts human eye features from the preprocessed human eye image signal, and calculate the human eye fatigue value; the fusion subunit fuses the EEG fatigue value and the human eye fatigue value, analyzes and calculates the fatigue level, and judges whether the meas...
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