The heartbeat is simultaneously a biological event, a medical signal, and a cultural object. This research investigates what happens when it becomes computational raw material, captured via ECG, translated into audio, and processed through machine learning synthesis (RAVE).
These outputs begin with my own cardiac data, a translation pipeline that produces three distinct sonic versions from a single heartbeat recording: an ambient atmospheric version, a percussive version, and a composite. A key early observation: the ML output flickers between recognisable traces of the original signal and something categorically different, a wavering between presence and absence that constitutes a first empirical encounter with what I am calling phygital vibration.
The research is developing toward two installation proposals and a PhD framework.