The present invention belongs to the technical field of biomedical signal processing analysis. Provided is a mental fatigue critical point calibration method based on self-organized criticality. A self-organized critical model is constructed by using a dynamic characteristic of a brain network so as to perform avalanche dynamics deduction of mental fatigue, which conforms to an internal mechanism of fatigue complexity evolution, such that a calibrated critical state is dynamically stable and has robustness. By means of the verification of behavior data, a mental fatigue critical state determined from two dimensions including physiology and behavior has relatively high reliability, and can provide support for guiding the setting of fatigue category labels, so as to achieve more accurate classification identification.
MENTAL FATIGUE CRITICAL POINT CALIBRATION METHOD BASED ON SELF-ORGANIZED CRITICALITY