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pub:research [2018/10/25 11:36] – CoSECiVi gjn | pub:research [2018/11/27 07:45] – [GEM2018] bgc | ||
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==== GEM2018 ==== | ==== GEM2018 ==== | ||
- | * //Emotion in models meets emotion in design: building true affective games//, Barbara Giżycka, Grzegorz J. Nalepa | + | * [[https:// |
* Presented at the [[http:// | * Presented at the [[http:// | ||
* Abstract: A relatively new field of research on affective gaming suggests applying affective computing solutions to develop games that can interact with the player on the emotional level. To bring together selected models of affect and affect-driven frameworks developed to date, we propose an approach based on affective design patterns. We build on the assumption that player’s emotional reactions to in-game events can be evoked by patterns used early in the design phase. We provide description of experiments conducted to test our hypothesis so far, along with some tentative observations, | * Abstract: A relatively new field of research on affective gaming suggests applying affective computing solutions to develop games that can interact with the player on the emotional level. To bring together selected models of affect and affect-driven frameworks developed to date, we propose an approach based on affective design patterns. We build on the assumption that player’s emotional reactions to in-game events can be evoked by patterns used early in the design phase. We provide description of experiments conducted to test our hypothesis so far, along with some tentative observations, | ||
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==== HSI2018 ==== | ==== HSI2018 ==== | ||
- | * // | + | * // |
* Presented at [[http:// | * Presented at [[http:// | ||
* Abstract: In the paper we describe a new software solution for mobile devices that allows for data acquisition from wristbands. The application reads physiological data from wristbands and supports multiple recent hardware. In our work we focus on the Heart Rate (HR) and Galvanic Skin Response (GSR) readings. This data is used in the affective computing experiments for human emotion recognition. | * Abstract: In the paper we describe a new software solution for mobile devices that allows for data acquisition from wristbands. The application reads physiological data from wristbands and supports multiple recent hardware. In our work we focus on the Heart Rate (HR) and Galvanic Skin Response (GSR) readings. This data is used in the affective computing experiments for human emotion recognition. |