Abstract
The pleasure that often comes with eating can be further enhanced with intelligent technology, as the field of human-food interaction suggests. However, knowledge on how to design such pleasure-supporting eating systems is limited. To begin filling this knowledge gap, we designed “GustosonicSense”, a novel gustosonic eating system that utilizes wireless earbuds for sensing different eating and drinking actions with a machine learning algorithm and trigger playful sounds as a way to facilitate pleasurable eating experiences. We present the findings from our design and a study that revealed how we can support the "stimulation", "hedonism", and "reflexivity" for playful human-food interactions. Ultimately, with our work, we aim to support interaction designers in facilitating playful experiences with food.
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Wang, Y., Obie, H. O., Li, Z., Salim, F. D., Grundy, J., & Mueller, F. (2024). GustosonicSense: Towards understanding the design of playful gustosonic eating experiences. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3613904.3642182
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