[Announcements] CFP: Special issue on Recognizing the State of Emotion, Cognition and Action from Physiological and Behavioural Signals (deadline extended to 13 Nov)

[Siyuan Chen]

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Call For Paper (all accepted paper may also be collected in a freely-downloadable e-Book):


Journals: Frontiers in Computer Science, Frontiers in Psychology

Special issue: Recognizing the State of Emotion, Cognition and Action from Physiological and Behavioural Signals

Deadline: 13 September 2021 13 November 2021



About this special issue:

Nowadays people spend significant amount of time interacting with devices and computing systems. These devices and computing systems, however, are playing a passive role during interaction, unlike humans who can observe partners to know when and how to provide assistance. Seamless blending of humans and technology for intelligent interaction is becoming more important than ever. One key aspect is to let machine understand users’ state of emotion, cognition and action (herein termed user state for simplicity). Building this ability in machine is of critical use in a wide variety of human machine collaboration contexts spanning from safe driving to assistance for people with disability. For example, autonomous car can ‘observe’ user’s state of emotion (e.g., negative), cognition (e.g., overloaded), and action (e.g., glancing down) to determine when to give safety reminders or take control. The aim of this research is to empower machine to understand user state so that human and machine can collaborate in the best form to augment human ability.


The main objective of this Research Topic is to bring together current advances in the field. Topics of interest include, but are not limited to:


• Theorical frameworks and/or experimental study or review for the relationship between user state and physiological/behavioural cues

• Methods for processing physiological and behavioural signals and recognizing state of emotion, cognition, and action indicators

• Machine learning techniques focused specifically on user state recognition

• Methods for multimodal user-state recognition

• Robustness issues in recognizing user state in less controlled contexts and everyday life.

• Wearable technologies for user state analysis

• Emotion/cognition/action recognition-powered assistive technologies and applications

• Novel user-state recognition systems and their applications

Link: https://www.frontiersin.org/research-topics/20500/recognizing-the-state-of-emotion-cognition-and-action-from-physiological-and-behavioural-signals<https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.frontiersin.org%2Fresearch-topics%2F20500%2Frecognizing-the-state-of-emotion-cognition-and-action-from-physiological-and-behavioural-signals&data=04%7C01%7C%7C1ddfa037e2bb49085ab108d8eec3a630%7C1faf88fea9984c5b93c9210a11d9a5c2%7C0%7C0%7C637521871373261444%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=PlO%2Bo2oZL%2BLAWJrtoy4Fe36vBmuBfclolb2T%2F6v5Qhc%3D&reserved=0>
Author guidelines: https://www.frontiersin.org/about/author-guidelines
Publishing fee: https://www.frontiersin.org/about/publishing-fees

Submission Deadlines
Manuscript Submission: 13 November 2021

Topic Editors
Dr. Siyuan Chen (University of New South Wales, Australia)
Dr. Youngjun Cho (University College London, United Kingdom)
Dr. Kun Yu (University of Technology Sydney, Australia)
Dr. Laura M. Ferrari (Université Côte d'Azur, France)
Dr. Francois Bremond (INRIA, France)



Dr. Siyuan Chen


Lecturer

School of Electrical Engineering & Telecommunications

UNSW, Sydney, NSW 2052, Australia

Email: siyuan.chen at unsw.edu.au

[cid:8e827e3e-61bb-4fb1-821a-fbb48df689ed]

CRICOS Provider Code 00098G


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