Sinestesia as a model for HCI: a Systematic Review
<|reference_start|>Sinestesia as a model for HCI: a Systematic Review: Synesthesia, conceived as a neuropsychological condition, may prove valuable in studying the interaction between humans and machines by analyzing the co-occurrence of sensory or cognitive responses triggered by a stimulus. In our approach, synesthesia is elevated beyond a mere perceptual-cognitive anomaly, offering insights into the reciprocal interaction between humans and the digital system, steering novel experimental design and enriching results interpretations.This review broadens the traditional scope, conventionally rooted in neuroscience and psychology, by considering how computer science can approach this condition. The interdisciplinary examination revolves around two primary viewpoints: one associating this condition with specific cognitive, perceptual, and behavioral anomalies, and the other acknowledging it as a prevalent human experience. Synesthesia, in this review, emerges as a significant model for Human Computer Interaction (HCI). The exploration of this specific condition aims to decipher how atypical pathways of perception and cognition can be encoded, empowering machines to actively engage in processing information from both the body and the environment. The authors attempt to amalgamate findings and insights from various disciplines, fostering collaboration between computer science, neuroscience, psychology, and philosophy.The overarching objective is to construct a comprehensive framework that elucidates how synesthesia and anomalies in information processing can be harnessed within HCI, with a particular emphasis on contributing to digital technologies for medical research and enhancing patients care and comfort. In this sense, the review endeavors also to fill the gap between theoretical understanding and practical application.<|reference_end|>
@article{corciulo2024sinestesia,
    title={Sinestesia as a model for HCI: a Systematic Review},
    author={Simona Corciulo and Mario Alessandro Bochicchio},
    journal={arXiv preprint arXiv:2404.09303},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.09303},
    primaryClass={cs.HC}
}