A Survey on Mobile Affective Computing
Shengkai Zhang, Pan Hui

TL;DR
This survey reviews recent advances in mobile affective computing, focusing on wearable devices and their role in capturing natural emotional responses outside social contexts.
Contribution
It provides a comprehensive overview of models, methodologies, and systems in mobile AC, highlighting recent progress and future challenges.
Findings
Mobile wearable devices enable natural emotion detection outside social settings.
Various models and systems have been developed for mobile affective computing.
Remaining challenges include improving accuracy and addressing ethical concerns.
Abstract
This survey presents recent progress on Affective Computing (AC) using mobile devices. AC has been one of the most active research topics for decades. The primary limitation of traditional AC research refers to as impermeable emotions. This criticism is prominent when emotions are investigated outside social contexts. It is problematic because some emotions are directed at other people and arise from interactions with them. The development of smart mobile wearable devices (e.g., Apple Watch, Google Glass, iPhone, Fitbit) enables the wild and natural study for AC in the aspect of computer science. This survey emphasizes the AC study and system using smart wearable devices. Various models, methodologies and systems are discussed in order to examine the state of the art. Finally, we discuss remaining challenges and future works.
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Taxonomy
TopicsEmotion and Mood Recognition · User Authentication and Security Systems · Innovative Human-Technology Interaction
