Perception begins where noisy measurements become usable observations.
Perception is the research pillar concerned with how the world, the body, and technical environments are measured, modeled, and made available for later inference. Neuroide treats perception as a rigorous engineering and scientific problem rather than a pre-processing step.
Signal theory, transforms, filtering, stochastic structure, and waveform analysis across serious sensing problems.
Cross-sensor observation, fused representations, missing-modality handling, and synchronized measurement systems.
Human physiological dynamics, multiscale regulation, and the interpretation of biosignals as partial observations of coupled systems.
Signals
Signal theory, biosignals, and the realities of noisy measurement.
Multimodal Sensing
Cross-modal measurement, sensor fusion, and robustness to missing channels.
Physiological Systems
Dynamic systems, regulation, and the scientific interpretation of biosignal data.
Multimodal Biosignal Foundation Models
Cross-modal pretraining and modality-robust physiological inference.
Physiological Signals as Dynamic Systems
An introduction to physiological data as observations of adaptive biological systems.