Classifying human emotions in HRI: applying global optimization model to EEG brain signals.

ABSTRACT: Significant efforts have been made in the past decade to humanize both the form and function of social robots to increase their acceptance among humans. To this end, social robots have recently been combined with brain-computer interface (BCI) systems in an attempt to give them an understanding of human mental states, particularly emotions. However, emotion recognition using BCIs poses several challenges, such as subjectivity of emotions, contextual dependency, and a lack of reliable neuro-metrics for real-time processing of emotions. Furthermore, the use of BCI systems introduces its own set of limitations, such as the bias-variance trade-off, dimensionality, and noise in the input data space. In this study, we sought to address some of these challenges by detecting human emotional states

SUBMITTER: Staffa M 

PROVIDER: S-EPMC10595007 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature