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Continuous, real-time emotion annotation: A novel joystick-based analysis framework

Sharma, Karan and Castellini, Claudio and Stulp, Freek and van den Broek, Egon (2017) Continuous, real-time emotion annotation: A novel joystick-based analysis framework. IEEE Transactions on Affective Computing, PP (99), p. 1. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/TAFFC.2017.2772882 ISSN 1949-3045

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Official URL: http://ieeexplore.ieee.org/document/8105870/

Abstract

Emotion labels are usually obtained via either manual annotation, which is tedious and time-consuming, or questionnaires, which neglect the time-varying nature of emotions and depend on human's unreliable introspection. To overcome these limitations, we developed a continuous, real-time, joystick-based emotion annotation framework. To assess the same, 30 subjects each watched 8 emotion-inducing videos. They were asked to indicate their instantaneous emotional state in a valence-arousal (V-A) space, using a joystick. Subsequently, five analyses were undertaken: (i) a System Usability Scale (SUS) questionnaire unveiled the framework's excellent usability; (ii) MANOVA analysis of the mean V-A ratings and (iii) trajectory similarity analyses of the annotations confirmed the successful elicitation of emotions; (iv) Change point analysis of the annotations, revealed a direct mapping between emotional events and annotations, thereby enabling automatic detection of emotionally salient points in the videos; and (v) Support Vector Machines (SVM) were trained on classification of 5 second chunks of annotations as well as their change-points. The classification results confirmed that ratings patterns were cohesive across the participants. These analyses confirm the value, validity, and usability of our annotation framework. They also showcase novel tools for gaining greater insights into the emotional experience of the participants.

Item URL in elib:https://elib.dlr.de/115348/
Document Type:Article
Title:Continuous, real-time emotion annotation: A novel joystick-based analysis framework
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sharma, KaranKaran.Sharma (at) dlr.dehttps://orcid.org/0000-0002-3323-7034
Castellini, ClaudioClaudio.Castellini (at) dlr.dehttps://orcid.org/0000-0002-7346-2180
Stulp, FreekFreek.Stulp (at) dlr.dehttps://orcid.org/0000-0001-9555-9517
van den Broek, Egonvandenbroek (at) acm.orghttps://orcid.org/0000-0002-2017-0141
Date:13 November 2017
Journal or Publication Title:IEEE Transactions on Affective Computing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:PP
DOI :10.1109/TAFFC.2017.2772882
Page Range:p. 1
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1949-3045
Status:Published
Keywords:Affective Computing, Emotion in human-computer interaction, Tools and methods of annotation, Time-series analysis, Changepoint analysis, Pattern Recognition
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Terrestrische Assistenz-Robotik
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Cognitive Robotics
Deposited By: Sharma, Karan
Deposited On:29 Nov 2017 16:15
Last Modified:31 Jul 2019 20:12

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