EEG Based Emotion Identification Using Unsupervised Deep Feature Learning

Xiang Li · Peng Zhang · Dawei Song · Guangliang Yu · Yuexian Hou · Bin Xiang Hu

67 citations0/0 files storedOpen Research Online - ORO (The Open University)

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Emotion and Mood Recognition EEG and Brain-Computer Interfaces Gaze Tracking and Assistive Technology

Abstract

Capturing user’s emotional state is an emerging way for implicit relevance feedback in information retrieval (IR). Recently, EEG-based emotion recognition has drawn increasing attention. However, a key challenge is effective learning of useful features from EEG signals. In this paper, we present our on-going work on using Deep Belief Network (DBN) to automatically extract high-level features from raw EEG signals. Our preliminary experiment on the DEAP dataset shows that the learned features perform comparably to the use of manually generated features for emotion recognition.

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References

1980A circumplex model of affect.2011DEAP: A Database for Emotion Analysis ;Using Physiological Signals 2014Feature Extraction and Selection for Emotion Recognition from EEG

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