Emotion Assessment: Arousal Evaluation Using EEG’s and Peripheral Physiological Signals

Multimedia Content Representation, Classification and Security - Lecture Notes in Computer Science ◽

10.1007/11848035_70 ◽

2006 ◽

pp. 530-537 ◽

Cited By ~ 133

Author(s):

Guillaume Chanel ◽

Julien Kronegg ◽

Didier Grandjean ◽

Thierry Pun

Keyword(s):

Physiological Signals ◽

Emotion Assessment

Download Full-text

Emotion Assessment From Physiological Signals for Adaptation of Game Difficulty

IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans ◽

10.1109/tsmca.2011.2116000 ◽

2011 ◽

Vol 41 (6) ◽

pp. 1052-1063 ◽

Cited By ~ 190

Author(s):

G. Chanel ◽

C. Rebetez ◽

M. Bétrancourt ◽

T. Pun

Keyword(s):

Physiological Signals ◽

Emotion Assessment

Download Full-text

Real-Time Emotion Assessment Method Based on Physiological Signals

2010 International Symposium on Computational Intelligence and Design ◽

10.1109/iscid.2010.147 ◽

2010 ◽

Cited By ~ 1

Author(s):

Qun Wu

Keyword(s):

Real Time ◽

Assessment Method ◽

Physiological Signals ◽

Emotion Assessment

Download Full-text

A dataset of continuous affect annotations and physiological signals for emotion analysis

Scientific Data ◽

10.1038/s41597-019-0209-0 ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 9

Author(s):

Karan Sharma ◽

Claudio Castellini ◽

Egon L. van den Broek ◽

Alin Albu-Schaeffer ◽

Friedhelm Schwenker

Keyword(s):

Real Time ◽

Temperature Sensors ◽

Physiological Signals ◽

Physiological Data ◽

Emotion Induction ◽

Annotation Data ◽

Problematic Issue ◽

Valence And Arousal ◽

Post Hoc ◽

Emotion Assessment

Abstract From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research, a direct and real-time inspection in realistic settings is not possible. Discrete, indirect, post-hoc recordings are therefore the norm. As a result, proper emotion assessment remains a problematic issue. The Continuously Annotated Signals of Emotion (CASE) dataset provides a solution as it focusses on real-time continuous annotation of emotions, as experienced by the participants, while watching various videos. For this purpose, a novel, intuitive joystick-based annotation interface was developed, that allowed for simultaneous reporting of valence and arousal, that are instead often annotated independently. In parallel, eight high quality, synchronized physiological recordings (1000 Hz, 16-bit ADC) were obtained from ECG, BVP, EMG (3x), GSR (or EDA), respiration and skin temperature sensors. The dataset consists of the physiological and annotation data from 30 participants, 15 male and 15 female, who watched several validated video-stimuli. The validity of the emotion induction, as exemplified by the annotation and physiological data, is also presented.

Download Full-text