The new era of empathetic machines

The new era of empathetic machines

Problem being addressed

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.

Solution

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 researchers elaborate on adopting a predictive approach in studying human emotional processing based on brain activity. The study aims to contribute to the predictive approach in neurophysiological research by applying machine learning algorithms to accommodate for the complexity of the recorded data and to guarantee a higher degree of generalizability.

Advantages of this solution

Lateralization of brain oscillations at specific frequency bands is an important predictor of self-reported empathy scores. The 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.

Solution originally applied in these industries

entertainment

Entertainment Industry

Possible New Application of the Work

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

Electronics and Sensors Industry

It could be used for enhancement of human-technology interaction, where artificial agents or systems are able to understand human affective state and personalize the interaction; the 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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Healthcare Sector

The possibility of observing and predicting human empathy on the basis of neural activity introduces a new method for emotion recognition and personality profiling. This approach can be used in providing support to individuals who struggle with social behavioural disorder that is fully adapted to their condition.

Author of original research described in this blitzcard:

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Name of the author who conducted the original research that this blitzcard is based on.

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