This paper validates the using a low-cost EEG headset – Emotiv Insight 2.0 – for detecting emotional responses to visual stimuli. The researchers detected, based on brainwave activity, the viewer’s emotional states in reference to a series of visuals and mapped them on valance and arousal axes. Valence in this research is defined as the viewer’s positive or negative state, and arousal is defined as the intensity of the emotion or how calm or excited the viewer is. A set of thirty images – divided into two categories: Objects and Scenes – was collected from the Open Affective Standard Image Set (OASIS) and used as a reference for validation. We collected atotal of 720 data points for six different emotional states: Engagement, Excitement, Fo...
The detection of a human face in a visual field and correct reading of emotional expression of faces...
[EN] As Virtual Reality (VR) is starting to be used to train emotional regulation strategies, it wou...
In this study, electroencephalography-based data for emotion recognition analysis are introduced. EE...
Emotion classification using electroencephalography (EEG) data and machine learning techniques have ...
Emotions are fundamental for human beings and play an important role in human cognition. Emotion is ...
[EN] New electroencephalography (EEG) devices, more portable and cheaper, are appearing on the marke...
Since the beginning of the 20th century, electroencephalography (EEG) has been used in a wide variet...
We present DREAMER, a multi-modal database consisting of electroencephalogram (EEG) and electrocardi...
Abstract A methodological contribution to a reproducible Measurement of Emotions for an EEG-based sy...
Emotion classification using electroencephalography (EEG) data and machine learning techniques have ...
Objective: This study investigated the relationship between emotions and brain signals evoked by veh...
Abstract Affective computing based on electroencephalogram (EEG) has gained increasing attention for...
The beauty of affective computing is to make machine more emphatic to the user. Machines with the ca...
Abstract: Our project focused on recognizing emotion from human brain activity, measured by EEG sign...
Emotion states greatly influence many areas in our daily lives, such as: learning, decision making a...
The detection of a human face in a visual field and correct reading of emotional expression of faces...
[EN] As Virtual Reality (VR) is starting to be used to train emotional regulation strategies, it wou...
In this study, electroencephalography-based data for emotion recognition analysis are introduced. EE...
Emotion classification using electroencephalography (EEG) data and machine learning techniques have ...
Emotions are fundamental for human beings and play an important role in human cognition. Emotion is ...
[EN] New electroencephalography (EEG) devices, more portable and cheaper, are appearing on the marke...
Since the beginning of the 20th century, electroencephalography (EEG) has been used in a wide variet...
We present DREAMER, a multi-modal database consisting of electroencephalogram (EEG) and electrocardi...
Abstract A methodological contribution to a reproducible Measurement of Emotions for an EEG-based sy...
Emotion classification using electroencephalography (EEG) data and machine learning techniques have ...
Objective: This study investigated the relationship between emotions and brain signals evoked by veh...
Abstract Affective computing based on electroencephalogram (EEG) has gained increasing attention for...
The beauty of affective computing is to make machine more emphatic to the user. Machines with the ca...
Abstract: Our project focused on recognizing emotion from human brain activity, measured by EEG sign...
Emotion states greatly influence many areas in our daily lives, such as: learning, decision making a...
The detection of a human face in a visual field and correct reading of emotional expression of faces...
[EN] As Virtual Reality (VR) is starting to be used to train emotional regulation strategies, it wou...
In this study, electroencephalography-based data for emotion recognition analysis are introduced. EE...