Physiological response is an important component of an emotional episode. In this paper, we introduce a Toolbox for Emotional feAture Extraction from Physiological signals (TEAP). This open source toolbox can preprocess and calculate emotionally relevant features from multiple physiological signals, namely, electroencephalogram (EEG), galvanic skin response (GSR), electromyogram (EMG), skin temperature, respiration pattern, and blood volume pulse. The features from this toolbox are tested on two publicly available databases, i.e., MAHNOB-HCI and DEAP. We demonstrate that we achieve similar performance to the original work with the features from this toolbox. The toolbox is implemented in MATLAB and is also compatible with Octave. We hope th...
From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research...
Emotion charting using multimodal signals has gained great demand for stroke-affected patients, for ...
This paper reviews emotion classification investigations, focusing on the use of the Electrocardiogr...
Many studies in literature successfully use classification algorithms to classify emotions by means ...
Little attention has been paid so far to physiological sig-nals for emotion recognition compared to ...
International audienceWith the development of wearable physiological sensors, emotion estimation bec...
Emotion recognition is an important pattern recognition problem that has inspired researchers for se...
Emotion modeling and identification has attracted substantial interest from disciplines including c...
© 2019 IEEE.Recently, there are various studies in the literature for emotion analysis by using phys...
The need to provide computers with the ability to distinguish the affective state of their users is ...
In recent years, research on emotion classification based on physiological signals has actively attr...
This project uses a galvanic skin response (GSR) signal to describe emotion recognition. Human being...
Changes or variation occur in physiological parameters of the body when a person is going through a ...
This paper aims at evaluating the performance of various emotion classification approaches from psyc...
This work addresses the still unsolved problem of stimulus- and subject-independent emotion identifi...
From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research...
Emotion charting using multimodal signals has gained great demand for stroke-affected patients, for ...
This paper reviews emotion classification investigations, focusing on the use of the Electrocardiogr...
Many studies in literature successfully use classification algorithms to classify emotions by means ...
Little attention has been paid so far to physiological sig-nals for emotion recognition compared to ...
International audienceWith the development of wearable physiological sensors, emotion estimation bec...
Emotion recognition is an important pattern recognition problem that has inspired researchers for se...
Emotion modeling and identification has attracted substantial interest from disciplines including c...
© 2019 IEEE.Recently, there are various studies in the literature for emotion analysis by using phys...
The need to provide computers with the ability to distinguish the affective state of their users is ...
In recent years, research on emotion classification based on physiological signals has actively attr...
This project uses a galvanic skin response (GSR) signal to describe emotion recognition. Human being...
Changes or variation occur in physiological parameters of the body when a person is going through a ...
This paper aims at evaluating the performance of various emotion classification approaches from psyc...
This work addresses the still unsolved problem of stimulus- and subject-independent emotion identifi...
From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research...
Emotion charting using multimodal signals has gained great demand for stroke-affected patients, for ...
This paper reviews emotion classification investigations, focusing on the use of the Electrocardiogr...