Toward EEG-Based Objective Assessment of Emotion Intensity.

Area of Science:

• Neuroscience
• Affective Science
• Computational Neuroscience

Background:

• Objective measurement of emotion dynamics is challenging due to limited methodologies.
• Existing emotion recognition models often lack temporal precision.
• Understanding real-time emotional responses is crucial for psychological and neurological research.

Purpose of the Study:

• To propose and validate a novel approach for tracking emotion intensity (EI) using electroencephalogram (EEG).
• To enhance the accuracy of EEG-based emotion recognition models by incorporating selective sampling strategies.
• To provide a reliable method for objectively evaluating the temporal dynamics of emotions.

Main Methods:

• Utilizing electroencephalogram (EEG) recordings during continuous affective stimulation.
• Developing selective sampling strategies to identify and leverage emotion-related EEG patterns.
• Validating the approach by assessing improvements in classifying arousal and valence.

Main Results:

• Demonstrated a significant association between selective sampling outcomes and prominent emotion-related EEG patterns.
• Achieved classification improvements of 2.01% for arousal and 1.71% for valence using the proposed method.
• Established a novel, objective measurement for profiling emotion dynamics.

Conclusions:

• The proposed intensity-selective sampling strategy offers a breakthrough in objectively evaluating emotion temporal dynamics.
• This method provides a promising avenue for refining EEG-based emotion recognition models.
• The findings contribute a reliable tool for future affective studies on emotion dynamics.