Bio-harmonic Quartet is a hybrid performance system that binds together a group of musicians and artists through a shared biofeedback network. This network functions as a collective musical interface, drawing on the bodily activity of each participant — muscle movement, pulse, and neural data — and channeling this information into machine learning models that generate music and soundscapes in real time. The result is a form of composition that belongs to no single author, emerging instead from the dynamic interplay between human physiology and machine intelligence.

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The work is an investigation into the possibilities of human-machine collaboration within the context of musical creation and live performance. It began as an inquiry into BCI and machine learning technologies, and the ways in which these systems might disrupt and evolve the practices of music production, composition, and performance. Building on the artist's earlier explorations of machine networks and human-machine interaction, the piece moves toward a more complex and integrated model — one in which humans and machines do not operate in opposition, but work in concert toward shared creative expression.

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The system consists of machine learning models paired with wearable sensory devices that capture biometric and neural data across all participants simultaneously. 

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Bio-harmonic Quartet was performed under the design collective name Dogma Lab.