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Toolbox for Emotional feAture extraction from Physiological signals (TEAP)

Villaro-Dixon, Frank
Published in Frontiers in ICT. 2017, vol. 4
Abstract 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 this toolbox to be further developed and accelerate research in affective physiological signal analysis.
Keywords Physiological signalsEmotionsAffective computingElectroencephalogram signalsPhysiological signal processingCode:MATLABCode:OctaveToolbox
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Research groups Affective sciences
Computer Vision and Multimedia Laboratory
(ISO format)
SOLEYMANI, Mohammad et al. Toolbox for Emotional feAture extraction from Physiological signals (TEAP). In: Frontiers in ICT, 2017, vol. 4. https://archive-ouverte.unige.ch/unige:91888

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Deposited on : 2017-02-16

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