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Wearable AI Early Warning System (2D)

A 2D digital-twin dashboard of a wearable AI patient-monitoring system: live ECG-style vital waveforms, a sensor-to-AI-core network diagram, and a trend-augmented early-warning score that predicts deterioration before fixed thresholds are crossed.

Digital Twins & Wearable Tech (IoT)2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

Details

CategoryDigital Twins & Wearable Tech (IoT)

RenderingCanvas 2D

DifficultyModerate

Target FPS60

ControlsSliders set the patient's baseline heart rate, SpO2, respiratory rate, temperature, the AI's trend sensitivity (kappa) and simulation speed; a toggle switches the AI trend term on/off, buttons inject a sepsis-like deterioration event or reset to stable, and the sensor-to-AI-core network diagram supports drag-to-pan and scroll/pinch-to-zoom.

AIwearablehealthcaredigital twinearly warningmonitoringECG waveformnetwork diagram

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This simulator builds a live 2D digital-twin dashboard of a patient wearing a continuous biosensor patch. Heart rate, SpO₂, respiratory rate and skin temperature stream as scrolling ECG-style waveforms while four sensor nodes feed a network diagram into an AI risk core — the same idea behind real hospital and home wearable AI monitoring platforms used for sepsis and post-operative deterioration detection. Adjust the patient's baseline vitals and the AI's trend sensitivity, inject a simulated deterioration event, and watch the risk score climb ahead of any single vital crossing a hard threshold on its own.

⚙ Under the hood

2D digital-twin dashboard of a wearable AI patient-monitoring system: scrolling ECG-style waveforms for heart rate, SpO2, respiratory rate and temperature feed a NEWS2-style base score, a live trend term you can tune with a kappa slider, and a pannable/zoomable sensor-to-AI-core network diagram — all detecting deterioration before any single vital crosses a fixed threshold.

AIwearablehealthcaredigital twinearly warningmonitoringECG waveformnetwork diagram

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install