Abstract: The present disclosure discloses an advanced mental fatigue early warning system, electronic device and storage medium, including a data acquisition module, a preprocessing module, an adjustment ability calculation module, a fatigue early warning module, a communication module and a storage module; the data acquisition module is configured for obtaining pupil diameter data; the preprocessing module is configured for preprocessing the pupil diameter data, removing invalid data, and performing linear interpolation; the adjustment ability calculation module is configured for performing calculation and correcting the preprocessed pupil diameter data; the fatigue early warning module is configured for performing mathematical modeling, establishing an advanced prediction model, and calculating a remaining time for an upcoming mental fatigue occurs and issuing an alarm; the communication module is configured for uploading mental fatigue adjustment abilities and alarm methods; the storage module is configured for arc

Abstract: The present disclosure provides a method and device for dynamic recognition of emotion based on facial muscle movement monitoring, including: obtaining muscle movement data on one side and continuous frame images on the other side; obtaining multiple emotional states related to emotions, associating each emotional state with its corresponding continuous frame images, associating each emotional state with the muscle movement data corresponding to the continuous frame images at the same location and at the same time, to form a training set, building an emotion recognition model; inputting the muscle movement data and continuous frame images obtained in real time into the emotion recognition model to obtain a corresponding emotional state. This method builds an emotion recognition model through muscle movement data and continuous frame image, and uses motion data to make up for the parts of small action images that cannot be collected, thereby obtaining accurate emotion detection results.