Creating generative data-driven aesthetics based on brain waves

dc.contributor.authorAzevedo, Bruno
dc.contributor.authorSilva, Hélder David Malheiro
dc.contributor.authorLapenta, Olivia Morgan
dc.contributor.authorPartesotti, Helena
dc.date.accessioned2025-11-21T12:58:19Z
dc.date.issued2026
dc.description.abstractContemplative 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.eng
dc.description.sponsorshipFCT -Fundação para a Ciência e a Tecnologia(UIDB/00319/2020)por
dc.distributioninternational
dc.identifier.citationAzevedo, B., Silva, H., Lapenta, O.M., Partesotti, E. (2026). Creating Generative Data-driven Aesthetics Based on Brain Waves. In: Brooks, A.L., Banakou, D., Ceperkovic, S. (eds) ArtsIT, Interactivity and Game Creation. ArtsIT 2024. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 651. Springer, Cham. https://doi.org/10.1007/978-3-031-97257-7_7
dc.identifier.doi10.1007/978-3-031-97257-7_7
dc.identifier.eisbn978-3-031-97257-7
dc.identifier.isbn978-3-031-97256-0
dc.identifier.issn1867-8211por
dc.identifier.urihttps://hdl.handle.net/1822/98244
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer, Cham
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-031-97257-7_7
dc.rightsrestrictedAccess
dc.rights.uriN/A
dc.subjectComputational Aestheticspor
dc.subjectEEG data-driven Visualizationpor
dc.subjectImmersive Environmentspor
dc.subjectZen Gardenspor
dc.titleCreating generative data-driven aesthetics based on brain waveseng
dc.typeconferencePaper
dspace.entity.typePublication
oaire.citation.conferenceDate2024-11
oaire.citation.conferencePlaceAbu Dhabi
oaire.citationEndPage111por
oaire.citationStartPage95por
oaire.citationVolume651 LNICSTpor
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
sdum.conferencePublication13th EAI International Conference: ArtsIT, Interactivity & Game Creation
sdum.journalLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST)por

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