Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing

Area of Science:

• Psychophysiology
• Neuroscience
• Biomedical Engineering

Background:

• Emotions involve complex physiological and psychological changes.
• Traditional body sensation maps rely on subjective self-reports.
• Existing research often overlooks peripheral nervous system contributions to emotional responses.

Purpose of the Study:

• To develop an objective method for mapping emotions using physiological signals.
• To investigate peripheral nervous system activity during emotional states.
• To create visualized bodily emotion maps from electrophysiological data.

Main Methods:

• Constructed a body surface potential mapping (BSPM) system.
• Induced negative and non-negative emotions in participants.
• Acquired high-density body surface potential data.
• Analyzed functional connectivity networks of body surface potentials (BSPs).

Main Results:

• Identified denser functional connectivity networks in BSPs during negative emotions.
• Developed emotion maps based on local clustering coefficient (LCC) consistent with subjective body sensation maps.
• Achieved an 80.77% classification accuracy for distinguishing negative from non-negative emotions.

Conclusions:

• High-density BSPs can objectively map emotional states.
• BSPM provides a novel approach for psychophysiological computing.
• This method enhances our understanding of the peripheral nervous system's role in emotion.