Prediction of Human Empathy based on EEG Cortical Asymmetry
- URL: http://arxiv.org/abs/2005.02824v1
- Date: Wed, 6 May 2020 13:49:56 GMT
- Title: Prediction of Human Empathy based on EEG Cortical Asymmetry
- Authors: Andrea Kuijt and Maryam Alimardani
- Abstract summary: lateralization of brain oscillations at specific frequency bands is an important predictor of self-reported empathy scores.
Results could be employed in the development of brain-computer interfaces that assist people with difficulties in expressing or recognizing emotions.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Humans constantly interact with digital devices that disregard their
feelings. However, the synergy between human and technology can be strengthened
if the technology is able to distinguish and react to human emotions. Models
that rely on unconscious indications of human emotions, such as
(neuro)physiological signals, hold promise in personalization of feedback and
adaptation of the interaction. The current study elaborated on adopting a
predictive approach in studying human emotional processing based on brain
activity. More specifically, we investigated the proposition of predicting
self-reported human empathy based on EEG cortical asymmetry in different areas
of the brain. Different types of predictive models i.e. multiple linear
regression analyses as well as binary and multiclass classifications were
evaluated. Results showed that lateralization of brain oscillations at specific
frequency bands is an important predictor of self-reported empathy scores.
Additionally, prominent classification performance was found during
resting-state which suggests that emotional stimulation is not required for
accurate prediction of empathy -- as a personality trait -- based on EEG data.
Our findings not only contribute to the general understanding of the mechanisms
of empathy, but also facilitate a better grasp on the advantages of applying a
predictive approach compared to hypothesis-driven studies in neuropsychological
research. More importantly, our results could be employed in the development of
brain-computer interfaces that assist people with difficulties in expressing or
recognizing emotions.
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