IEEE WCCI 2014, IEEE World Congress on Computational Intelligence,

Hybrid Systems Special Session on

Computational Intelligence for Physiological and Affective Computing (CIPAC)

July 6-10, 2014, Beijing, China


Special session objectives and topics

Affective Computing (AC) is “computing that relates to, arises from, or deliberately influences emotions,” as initially coined by Professor R. Picard (Media Lab, MIT). It has been gaining popularity rapidly in the last decade because it has great potential in the next generation of human-computer interfaces. One goal of affective computing is to design a computer system that responds in a rational and strategic fashion to real-time changes in user affect (e.g., happiness, sadness, etc), cognition (e.g., frustration, boredom, etc.) and motivation, as represented by speech, facial expressions, physiological signals, neurocognitive performance, etc.

Physiological Computing (PC) relates to computation that incorporates physiological signals in order to produce useful outputs (e.g., in computer-human interaction). It mainly differs from AC in the sense that its foremost focus is not the modeling of affect but rather the utilization of physiological information generally.


AC/PC raise many new challenges for signal processing, machine learning and computational intelligence. Fuzzy Logic Systems in particular provide a highly promising avenue for addressing some of the fundamental research challenges in AC/PC where most data sources such as: body signals (e.g., heart rate, brain waves, skin conductance and respiration) facial features, speech and human kinematics are very noisy/uncertain and subject-dependent. Clearly however, other key areas of CI research, such as evolutionary learning algorithms and neural network based classifiers provide essential tools to address the significant challenge of AC/PC.


The Computational Intelligence and Physiological and Affective Computing special session aims to bring together researchers from the three areas of CI to discuss how CI techniques can be used individually or in combination to help solve challenging AC/PC problems, and conversely, how physiological and affect (emotion) and its modeling can inspire new approaches in CI and its applications. Topics of interest for this special session include but are not limited to:


·         Models of emotion and physiological information

·         Classifiers for physiological information

·         Applications based on/around physiological information

·         Fuzzy set and system based architectures for processing emotions and other affective states

·         Automatic emotion recognition & synthesis from physiological signals, facial expressions, body language, speech, or neurocognitive performance

·         Emotion mining from texts, images, or videos

·         Affective interaction with virtual agents and robots based on fuzzy systems

·         Applications of affective computing in interactive learning, affective gaming, personalized robotics, virtual reality, social networking, smart environments, healthcare and behavioral informatics, etc.

Contact email:


Session Organisers

Dr Christian Wagner
Horizon Digital Economy Research
& School of Computer Science
University of Nottingham,
Nottingham NG7 2TU
Phone: +44 115 74 84023
Fax: +44 115 82 32551


Dr Dongrui Wu
Machine Learning Lab
GE Global Research
Niskayuna NY 12065
Phone: +1-213-595-3269


Dr Faiyaz Doctor
Intelligent Informstion Modelling and Retriveal Group
Faculty of Engineering and Computing
Coventry University
Phone: +44 24 7688 8848