Demo: Sensing gamers' emotions using physiological sensors
Understanding emotions of gamers can benefit game designers in various ways. How gamers feel while they playing a game can be treated as valuable user feedback to improve the development process of that game. Sensing player emotions also enables game designers to create adaptive game that can adjust...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2016
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/3280 https://ink.library.smu.edu.sg/context/sis_research/article/4282/viewcontent/9924487.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Understanding emotions of gamers can benefit game designers in various ways. How gamers feel while they playing a game can be treated as valuable user feedback to improve the development process of that game. Sensing player emotions also enables game designers to create adaptive game that can adjust itself to provide best gaming experience based on player emotions. However, how to effectively evaluate emotions of gamers is still an open research challenge. Two common techniques to evaluate emotional state are using self-assessments such as questionnaires or interviews, and to recognize expressed emotions by analyzing videos or images of facial expression, body languages, and gesture. Although the self-report approach is convenient and unobtrusive, it requires users' cognitive attention. The vision-based approach also has some drawbacks that users' expressions do not necessarily reflect what they actually feel and there is also concern about privacy as images of users are captured. In this work, we implement Jasper, a system using on wearable physiological sensors to recognize emotions of gamers. Compared to the mentioned approaches, physiological sensors system can recognize emotions continuously without interrupting user experience. Moreover, the physiological signals are involuntary and mostly activated by the Autonomic Nervous System, which are useful to detect actual emotions and robust to expression manipulation (e.g. social making). The contribution of this work is to demonstrate the feasibility of using commodity and unobtrusive wearable biosensors to recognize mobile gamer emotions. |
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