An EEG-based framework for exploring adaptive rhythmic human-machine interaction

descriptionPublicationkeyboard_double_arrow_right Preprint 09 Mar 2026Publisher:Ghent University Department of Information technology, Hearing technology & Acoustics Research @ Waves.

Authors: Van Ransbeeck, Wannes; Yuan, Zhongju; Maes, Pieter-Jan; Leman, Marc; Verhulst, Sarah; Botteldooren, Dick;

doi: 10.5281/zenodo.18922420 , 10.5281/zenodo.18922421

An EEG-based framework for exploring adaptive rhythmic human-machine interaction

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Abstract

This article contains the preprint of the to-be-published article on human-human and human-machine interaction within ecologically valid rhythmic interactions.It addresses the shortcomings of typical paradigms in rhythmic interaction research and proposes a mobile yet controlled EEG framework for exploring these interactions.

Keywords

Rhythm Interaction, AI, Adaptive Systems, EEG, Ecological Validity

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