The increasing instance of negative emotion reduce the performance of emotion recognition

Abstract

IntroductionEmotion recognition plays a crucial role in affective computing. Recent studies have demonstrated that the fuzzy boundaries among negative emotions make recognition difficult. However, to the best of our knowledge, no formal study has been conducted thus far to explore the effects of increased negative emotion categories on emotion recognition.MethodsA dataset of three sessions containing consistent non-negative emotions and increased types of negative emotions was designed and built which consisted the electroencephalogram (EEG) and the electrocardiogram (ECG) recording of 45 participants.ResultsThe results revealed that as negative emotion categories increased, the recognition rates decreased by more than 9%. Further analysis depicted that the discriminative features gradually reduced with an increase in the negative emotion types, particularly in the θ, α, and β frequency bands.DiscussionThis study provided new insight into the balance of emotion-inducing stimuli materials.

Synchronous hybrid brain–computer interfaces for recognizing emergency braking intention

“…From the above computations, we obtained the distance correlation coefficient of the f th feature between the feature matrix and the reference matrix using Equation (10).…”

“…Brain-computer interface (BCI) technology can directly communicate between the user's brain and computer-related devices and has been widely applied in the abovementioned and related studies. [8][9][10] Specifically, BCIs have played a considerable role in the research of detecting/predicting driver states and behaviors. BCI-based drowsiness recognition systems have been established to detect driver states to alert drivers to enter the awake state, thus considerably alleviating the occurrence of RTAs.…”