Digital Twin Documentation

01 Overview

The Real-Time Patient Digital Twin Generator is an AI-driven clinical simulation engine that creates a dynamic, physiology-based virtual replica of a patient.

RT-PDTG is designed for medical education — students, residents, and healthcare professionals can practice clinical decision-making in a safe, interactive environment. Unlike text-based case studies, the system simulates real-time physiological responses to disease progression and clinical interventions.

The platform covers 7 medical specialties with 90+ enriched patient cases, simulates 13 real-time vitals with live trend charts, tracks 5 physiological systems, renders 15 dynamic ECG waveform patterns, and provides comprehensive post-simulation evaluation with in-app adaptive learning.

02 How It Works

The simulation engine operates on a continuous 1-second tick cycle. Each tick, the physiology engine:

1. Calculates disease progression — the underlying condition advances based on time and severity
2. Applies intervention effects — any medications, fluids, or procedures modify physiological variables
3. Computes interdependencies — changes cascade across interconnected systems (e.g., hypotension → renal failure)
4. Updates vitals — all 13 monitored parameters are recalculated and displayed
5. Evaluates system status — each of the 5 physiological systems is classified as Normal, Stressed, or Critical

03 User Flow

04 Physiology Engine

The physiology engine is the heart of RT-PDTG. It uses a deterministic + probabilistic modeling approach, functioning as a state machine where each patient state is computed from the previous state plus environmental changes.

• Structured Patient State Object — All data stored in a JSON-based state object with vitals, system statuses, active medications, and history
• Parametrized Disease Models — Each specialty case has modeled progression rates, severity curves, and expected physiological impacts
• Continuous Time Simulation — 1-second simulation ticks ensure smooth, realistic vital sign changes
• Event-Driven Architecture — State changes emit events that trigger UI updates, log entries, and cascade effects

05 Vitals & Parameters

The system monitors 13 physiological parameters in real time:

06 Interdependency Modeling

The engine models causal relationships between physiological variables. When one parameter changes, it cascades to affect others:

• Hypotension → Renal Failure — MAP below 65 mmHg reduces renal perfusion, causing creatinine to rise
• Hypoxia → Tachycardia — SpO₂ below 90% triggers compensatory heart rate increase and metabolic acidosis
• Insulin → Glucose + Potassium — Insulin administration drops glucose and shifts potassium intracellularly
• Rising Creatinine → Hyperkalemia — Renal failure prevents potassium excretion
• Low GCS → Respiratory Instability — Decreased consciousness impairs respiratory drive

07 Physiological Systems

Five organ systems are continuously monitored and classified into three states:

• 🟢 Normal — Parameters within acceptable range
• 🟡 Stressed — Compensatory mechanisms active, early warning
• 🔴 Critical — System failure imminent, requires immediate intervention

08 Medical Specialties

Each specialty features unique case presentations, pathology models, and expected management protocols:

Example Cases

• Cardiology — STEMI: ST-elevation MI with chest pain, ECG changes, troponin elevation
• Pulmonology — Pulmonary Embolism: Acute dyspnea, hypoxemia, tachycardia
• Endocrinology — DKA: Diabetic ketoacidosis with hyperglycemia, metabolic acidosis
• Sepsis — Septic Shock: Systemic infection with SIRS criteria, organ dysfunction cascade
• Emergency — Hemorrhagic Shock: Trauma with blood loss, tachycardia, hypotension
• Neurology — Stroke: Acute focal deficit with altered GCS, BP management
• Nephrology — AKI: Acute kidney injury with rising creatinine, hyperkalemia

09 Intervention Engine

The intervention engine allows users to manage the virtual patient through 6 categories:

• Medications — Dose-based drugs with onset delay, peak effects, and duration
• IV Fluids — Crystalloids and colloids affecting intravascular volume
• Procedures — Intubation, chest tube, CPR, defibrillation
• Oxygen Therapy — Nasal cannula, face mask, non-rebreather, BiPAP
• Imaging — X-Ray, CT, MRI, Ultrasound with case-specific findings
• Lab Orders — CBC, BMP, ABG, Troponin, Blood Culture, etc.

10 Medications

Each medication has a modeled pharmacological profile:

11 Adverse Events

The system simulates adverse events when medications are mismanaged:

• Morphine Overdose — Respiratory depression (RR drops significantly, SpO₂ falls)
• Insulin-Induced Hypoglycemia — Glucose drops below 60 mg/dL, altered consciousness
• Epinephrine Arrhythmia — Excessive catecholamine causes tachyarrhythmia
• Nitroglycerin Hypotension — Over-vasodilation causing dangerous BP drop
• Heparin Bleeding — Excessive anticoagulation risk

12 Lab & Imaging Orders

Users can order diagnostic tests that produce case-specific results after a realistic processing delay:

Laboratory Tests

• CBC — Complete Blood Count (WBC, Hgb, Platelets)
• BMP — Basic Metabolic Panel (Na, K, BUN, Creatinine, Glucose)
• Troponin — Cardiac biomarker (elevated in MI)
• ABG — Arterial Blood Gas (pH, PaO₂, PaCO₂, HCO₃⁻)
• D-Dimer — Coagulation marker (elevated in PE, DVT)
• Blood Culture — Microbiological culture for sepsis workup

Imaging Studies

• Chest X-Ray — PA & lateral views for pulmonary/cardiac pathology
• CT Scan — Computed tomography for detailed cross-sectional imaging
• CT Pulmonary Angiography — CTPA for pulmonary embolism diagnosis
• MRI — Magnetic resonance for soft tissue detail
• Ultrasound / FAST — Focused assessment for trauma and effusions
• 12-Lead ECG — Electrocardiogram for rhythm and ischemia analysis

13 Dynamic ECG Monitor

The ECG monitor renders diagnosis-specific waveforms in real time using Gaussian pulse synthesis. Each patient case has a mapped ECG pattern.

ECG Pattern Types (15 total)

Dynamic Features

• Heart Rate Response — Waveform speed scales with live HR
• R-R Irregularity — AFib shows truly irregular beat spacing (35% variability)
• Baseline Wander — VFib/AFib patterns include fibrillatory noise
• QRS Width Variation — LBBB and VT patterns show widened QRS complexes
• Leading Dot Glow — Green glow dot follows the current trace position

14 Vitals Trend Charts

The dashboard includes real-time trend charts for four critical vitals, rendered using HTML Canvas:

• Heart Rate (HR) — Red line chart with alert zones at <50 and >120 bpm
• Blood Pressure (BP) — Dual orange lines showing systolic + diastolic
• SpO₂ — Cyan line chart with alert zone below 92%
• Respiratory Rate (RR) — Green line chart with alert zones at <10 or >28/min

Technical Details

• Rolling Window — Shows the last 60 data points
• Gradient Fill — Translucent gradient beneath each line
• Threshold Zones — Dashed red lines mark danger thresholds
• High-DPI Rendering — Canvas scales to device pixel ratio

15 AI Clinical Assistant

The floating AI assistant provides context-aware clinical support during simulations:

• "What is the diagnosis?" — Provides differential diagnosis based on current vitals
• "Treatment guidelines" — Evidence-based management protocols (ACC/AHA, GOLD, ADA, etc.)
• "Current vitals" — Summarizes the patient's current physiological state
• "Explain the pathophysiology" — Describes the mechanism of disease
• "How are the organ systems?" — Reports status of all 5 physiological systems

16 Evaluation & Clinical Reasoning

After ending a simulation, users receive a comprehensive Simulation Debrief:

Management Score

A 0–100 score with letter grade (A+ through F) based on clinical actions, timing, and appropriateness.

Actions Timeline

Chronological listing of every medication, procedure, and order with timestamps.

Clinical Feedback

Item-by-item assessment — marked as correct (✓), incorrect (✗), or cautionary (⚠). Each item explains why.

Clinical Reasoning Analysis

• Reasoning Score — Measures diagnostic thinking quality
• Time to First Intervention — How quickly the student began treating
• Diagnosis Identified — Whether the student's actions suggest correct diagnosis
• Physiological Outcome — Start vs. end vital comparison
• Evidence-Based Guidelines — Links actions to published clinical practice guidelines

Patient Cases — Field Reference Guide

Complete reference for every field in the Patient Cases collection. Explains what each field means, what values it expects, and how it affects the simulation.

{"hr":98,"sbp":105,"dbp":65,"map":78,"spo2":94,"rr":22,"temp":37.1,"gcs":15,"co":4.5,"pao2":85,"paco2":38,"glucose":110,"potassium":4.2,"lactate":2.1,"creatinine":1.0,"bicarb":22}

{"hr":0.3,"sbp":-0.5,"dbp":-0.3,"spo2":-0.1,"rr":0.1,"temp":0,"gcs":-0.05,"co":-0.02,"pao2":-0.1,"glucose":0,"potassium":0.01,"lactate":0.03,"creatinine":0,"bicarb":-0.02}

{
  "troponin": {"val": "2.1 ng/mL", "ref": "<0.04", "status": "critical"},
  "wbc": {"val": "12.4 ×10³/µL", "ref": "4.5-11.0", "status": "high"},
  "glucose": {"val": "195 mg/dL", "ref": "70-100", "status": "high"},
  "potassium": {"val": "5.8 mEq/L", "ref": "3.5-5.0", "status": "critical"},
  "creatinine": {"val": "1.0 mg/dL", "ref": "0.6-1.2", "status": "normal"}
}