Advances in Emotion Recognition Based on EEG Signal Analysis
Emotion recognition is a technique for recognizing and understanding human emotional states by analyzing physiological signals,and is widely used in clinically assisted diagnosis and treatment,social media,and human-computer interaction.Compared with other non-physiological signals,emotion recognition using electroencephalogram(EEG)can obtain more objective and direct emotion data.In this paper,we analyze the related research in domestic and international literature in recent years,and summarize the research progress of emotion recognition from four aspects,emotion data source and preprocessing,feature extraction,deep learning algorithm-based recognition model and clinical application.Among them,feature extraction and recognition based on deep learning algorithm play an important role in EEG signal analysis and emotion recognition.Finally,paper summarizes the clinical application and research status of emotion recognition based on EEG;and puts forward the outlook of future emotion recognition research in terms of solving the problem of data loss and establishing effective algorithms.
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