Nervous emotion intensity identification system and information processing method based on multiple physiological parameters

Abstract

The invention relates to the field of emotion recognition, in particular to a nervous emotion intensity identification system and an information processing method based on multiple physiological parameters. The information processing method includes the steps of offline training and online monitoring, wherein the offline training includes the processes of inducing users' nervous emotions, collecting users' multiple physiological signals and carrying out signal processing; the signal processing includes the processes of preprocessing, feature extraction and pattern recognition; the preprocessing includes the processes of suppressing power frequency interference for EEG signals by an adaptive filter, removing the power frequency interference by a band pass filter after amplifying the ECG, respiration and skin electrical signals, and intercepting valid data by an information processing tool. The nervous emotion intensity identification system and the information processing method have the advantages of collecting central nervous signals and autonomic nerve signals that reflect the nervous system information of the human body, establishing a classification model for people or individuals by offline training to carry out the real-time recognition and detection on the intensity of the users' nervous emotions, warning for the nervous emotions of excessive intensity, storing the users' emotional physiological signals in the whole process, and detecting the intensity of the users' nervous emotions in real time.

Description

technical field [0001] The invention belongs to the field of emotion recognition, and in particular relates to a stress intensity recognition system based on multiple physiological parameters and an information processing method applied to special working groups. Background technique [0002] Emotion recognition is a research hotspot in the fields of psychology and engineering, and has broad application prospects in human-computer interaction, distance education, etc. Deterioration of the mental state; in the process of human-computer interaction, the recognition of the user's emotional state can effectively improve the user experience; in the field of distance education, real-time emotion recognition can help improve the user's learning effect, etc. At present, there are two main methods of emotion recognition: recognition based on non-physiological signals (including facial expressions, voice or body gestures, etc.) and recognition based on physiological signals (including...

AI Technical Summary

Problems solved by technology

[0003] Although emotion recognition has made many achievements as a research hotspot in many fields, the current research on emotion recognition mainly focuses on the recognition of emotion types, such as the recognition of happiness, fear, sadness, etc., and few single emotion types, especially is to recognize the different intensities of tension

[0004] In real life, nervousness plays an important role. Almost everyone has the experience of nervousness during exams, inte...

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