The demo below is a conceptual, synthetic-data illustration of the closed adaptive loop: it senses physiological signals, infers an arousal state via a simple inspectable rule, adapts a stylized intervention, and re-senses — continuously. Inject a stress event and toggle Adaptive ON / OFF to watch the loop either regulate back to baseline or let the perturbation linger. Everything is generated in your browser; no real sensor or patient data is used.
XR + Multimodal Biosensing · Adaptive Systems
Closed-Loop Biosensing-Adaptive Intervention (illustrative simulation)
A conceptual, synthetic-data illustration of the sense → infer → adapt → sense loop central to my work in XR and multimodal biosensing for non-pharmacological pain and anxiety intervention. No real sensor or patient data is used.
Signals — synthetic, scrolling
Generated in-browser from a latent arousal state; axes plausible but illustrative.
State inference
Transparent rule — no black box.
ẼDA 0.00 · R̃MSSD 1.00
state = elevated when index > 50; target ≈ 26
Adaptive intervention — reacts to inferred state
When arousal climbs the intervention responds; the index then trends back toward baseline — closing the loop.