Transactions on Affective Computing

IEEE Transactions on Affective Computing (TAC) is intended to be a cross disciplinary and international archive journal aimed at disseminating results of research on the design of systems that can recognize, interpret, and simulate human emotions and related affective phenomena. Read the full scope of TAC


Expand your horizons with Colloquium, a monthly survey of abstracts from all CS transactions!


From the April-June 2018 issue

ASCERTAIN: Emotion and Personality Recognition Using Commercial Sensors

By Ramanathan Subramanian, Julia Wache, Mojtaba Khomami Abadi, Radu L. Vieriu, Stefan Winkler, and Nicu Sebe

Featured article thumbnail image We present ASCERTAIN—a multimodal databaASe for impliCit pERsonaliTy and Affect recognitIoN using commercial physiological sensors. To our knowledge, ASCERTAIN is the first database to connect personality traits and emotional states via physiological responses. ASCERTAIN contains big-five personality scales and emotional self-ratings of 58 users along with their Electroencephalogram (EEG), Electrocardiogram (ECG), Galvanic Skin Response (GSR) and facial activity data, recorded using off-the-shelf sensors while viewing affective movie clips. We first examine relationships between users’ affective ratings and personality scales in the context of prior observations, and then study linear and non-linear physiological correlates of emotion and personality. Our analysis suggests that the emotion-personality relationship is better captured by non-linear rather than linear statistics. We finally attempt binary emotion and personality trait recognition using physiological features. Experimental results cumulatively confirm that personality differences are better revealed while comparing user responses to emotionally homogeneous videos, and above-chance recognition is achieved for both affective and personality dimensions.

download PDF View the PDF of this article      csdl View this issue in the digital library


Editorials and Announcements

Announcements

  • According to Clarivate Analytics' 2016 Journal Citation Report, TAC has an impact factor of 3.149.
  • Heartfelt congratulations are offered to Georgios N. Yannakakis and Julian Togelius, authors of "Experience-Driven Procedural Content Generation," who were presented with TAC's Most Influential Paper Award by Editor-in-Chief Björn W. Schuller at the 2015 6th AAAC Affective Computing and Intelligent Interaction Conference in Xi'An, P.R. China on 22 September 2015.

Editorials


Guest Editorials


Reviewers List


Author Index


Access recently published TAC articles

RSS Subscribe to the RSS feed of recently published TAC content

mail icon Sign up for e-mail notifications through IEEE Xplore Content Alerts

preprints icon View TAC preprints in the Computer Society Digital Library


TAC -- Call for Papers cover

View the PDF of TAC's ongoing call-for-papers.

TAC is indexed in ISI