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Creating Generative Data-driven Aesthetics Based on Brain Waves
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DOI：10.1007/978-3-031-97257-7_7.png)
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Abstract
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Contemplative environments can significantly impact our mental health, and recent research highlights their importance for well-being. Guided by the principles and aesthetics of Zen Gardens and Zen Buddhism, the medium-term objective is to create an immersive, therapeutic environment with restorative qualities, utilizing a data-driven generative approach. This paper explores the initial phase of translating brain wave data, specifically electroencephalographic recordings of brain waves, into dynamic abstract visual patterns. In this process, the data serves as the pigment, while algorithms shape the visual aesthetics. In this first iteration, a dataset related to the research of brain activity in a resting-state experiment was used, and a Fast Fourier Transform was implemented in the Processing programming language to calculate the average amplitude and frequency. The average amplitude was used as input for the Flow Field algorithm, influencing the velocity visualized through dynamic curves with fading trails. By presenting the current work, this article aims to show the transformative potential of generative art in creating abstract immersive environments.
Keywords:
EEG data-driven Visualization
Computational Aesthetics
Immersive Environments
Zen Gardens
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Cited Papers
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