2021 - 5th International Workshop on Emotion Awareness for Pervasive Computing with Mobile and Wearable Devices

An important goal of pervasive computing is to integrate computer devices into the users’ everyday life
seamlessly. This allows context-aware applications to gather information about the users to support
them in their daily tasks. A newly attractive source of information for pervasive computing is provided
by mobile devices, wearable devices, and pervasive sensors able to detect the emotional state of the
users. In many real-world scenarios, it is essential to use wearable sensors, embedded in mobile devices
such as smartphones and smartwatches, to measure the emotional state of the user. This would help to
understand how emotions influence processes such as decision making and reasoning. However,
emotion recognition remains to be a complex and challenging task mainly regarding the following
aspects: sensing modalities, data analysis, and its application in real life.
• Sensing Modalities – what to sense and what kind of sensors can be used? Physical sensors in mobile
devices or biosensors in wearable devices and pervasive sensors (e.g. RF sensors) are currently
available.
• Data analysis – different approaches to emotion recognition are based on different types of collected
data.
• Application – how to effectively use the emotion information in pervasive computing and contextaware applications.
While there have been, many contributions targeting some of these challenges, there are still unsolved
problems. The proposed workshop will explore the challenges of the sensing, modelling, and
recognizing of emotions by using embedded sensors in smartphones, in wearable devices, and pervasive
sensors (e.g. RF sensors) for pervasive computing. We aim to have unique contributions addressing
these challenges and to provide a discussion space to facilitate collaboration among researchers
interested in emotion recognition for pervasive computing.
Topics of interests include, but are not limited to the following areas:
• Theory, experimental design, computational models, algorithms, and evolutional investigation in
emotion detection for pervasive computing.
• Emotion representations and signal characteristics that describe and identify emotions or stress.
• Mobile data measurement and collection platforms for emotion detection.
• Approaches to obtaining reliable ground truth and affective data annotation for emotion research.
• Emotion detection algorithms/approaches using data collected with mobile devices, wearable
devices and pervasive sensors (e.g. RF sensors)
• User studies and evaluation techniques for emotion detection and automated systems that model
and detect emotions.
• Awareness of emotions in collaboration or crowdsourcing.
• The novel use of emotion information in pervasive computing applications.
• The application of emotion information for the work-life balance, for a healthier life and behavior.
• The combined research of emotion recognition and artificial intelligence (AI).
• The investigation of the human-robot interaction.
• Privacy issues
• Presentation of emotions
• Applications of emotions
• Integration of emotions into lifelogging applications
• Emotions for Human Robot Interaction.
• Beyond traditional 'Sensing - Analysis - Feedback’