Adaptive Interface with Machine Learning and Biofeedback

This patent family describes systems and methods in which a digital interface continuously adapts its output — visuals, typography, pacing, audio — based on machine learning applied to sensor-captured physiological signals such as breathing and pulse. The underlying proposition is the inverse of the attention economy: rather than the person adjusting to a fixed interface, the interface adjusts to the measurable state of the person using it.

The claims grew directly out of the mYndful and Metaverses biofeedback research (2014–2016) and the immersive works that followed. They describe an engineering architecture, not a medical device: the documents cover signal capture, model-driven personalization and output adaptation. Adaptation to a measured signal is not a diagnosis, and nothing here is a diagnostic or clinical claim.

Inventor records list the legal name Hannes Bendfeldt, the same person publishing and exhibiting as Hannes Bend. Patent status, assignee and jurisdiction details are authoritative only in the official records linked below.