Interface with surgical robotics repositories#23
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Implements complete interface framework for integrating Multi-Heart-Model physiological simulations with major surgical robotics platforms. New interfaces: - dVRK (da Vinci Research Kit) with cisst-SAW support - CRTK (Collaborative Robotics Toolkit) standardized API - AMBF (Asynchronous Multi-Body Framework) simulator - ROS2 communication bridge for middleware integration - Physiological controller for adaptive robot control Key features: - Real-time physiological monitoring (HR, BP, SpO2, etc.) - Multi-level safety alerts (Normal/Caution/Warning/Critical) - Adaptive control parameter modulation based on patient state - Emergency stop triggers for critical physiological conditions - Surgical phase awareness (Approach/Manipulation/Retraction) - Heart rate variability (HRV) metrics computation - ROS/ROS2 message formatting and publishing - Workspace and velocity safety limits - Force/torque control with physiological scaling Module structure: - src/surgical_robotics/dvrk_interface.py (520+ LOC) - src/surgical_robotics/crtk_interface.py (480+ LOC) - src/surgical_robotics/ambf_interface.py (380+ LOC) - src/surgical_robotics/ros2_bridge.py (420+ LOC) - src/surgical_robotics/physio_controller.py (460+ LOC) Testing & Documentation: - Comprehensive test suite in tests/surgical_robotics/ - Complete integration demo in examples/surgical_robotics_demo.py - Full documentation in docs/SURGICAL_ROBOTICS_INTEGRATION.md Integration with HBCM: - PhysiologicalController accepts HeartBrainCouplingModel instance - Real-time extraction of heart rate and cardiovascular metrics - Closed-loop feedback between physiology and robot control - Stress and pain indices influence robot behavior Safety features: - Workspace boundary enforcement - Velocity and force scaling based on vital signs - Multi-level alert system with progressive response - Emergency stop on critical physiological thresholds - Surgical phase-specific constraints References: - Kazanzides et al. (2014) dVRK paper - Kazanzides et al. (2021) CRTK paper - Munawar et al. (2019) AMBF paper - ROS 2 and surgical robotics standards This implementation enables physiologically-aware robotic surgery with adaptive control that responds to patient state in real-time.
…egrations Implements all major missing cardiac models from roadmap plus comprehensive integration guide for surgical robotics and cardiac modeling platforms. New Cardiac Models (5 models, ~1,500 LOC): 1. Luo-Rudy Dynamic (LRd) Model (480 LOC) - Comprehensive guinea pig ventricular action potential - 11 state variables with full ionic currents - INa, ICaL, IK, IK1, IKp, pumps, exchangers - Intracellular Ca2+ dynamics with SR - APD calculation methods - Reference: Luo & Rudy (1994) Circ Res 2. Ten Tusscher-Panfilov 2006 Model (320 LOC) - Modern human ventricular electrophysiology - 18 state variables - Detailed ionic currents (INa, Ito, ICaL, IKr, IKs, IK1) - Cell type variants (endo/epi/M cell) - Widely used for arrhythmia studies - Reference: ten Tusscher & Panfilov (2006) Am J Physiol 3. O'Hara-Rudy 2011 (ORd) Model (290 LOC) - CiPA standard for cardiac drug safety - 19 state variables - Human ventricular action potential - FDA-approved for proarrhythmia assessment - Cell type variants (endo/epi/M cell) - Reference: O'Hara et al. (2011) PLoS Comput Biol 4. Courtemanche Atrial Model (310 LOC) - Human atrial electrophysiology - 21 state variables - Atrial fibrillation studies - IKur (atrial-specific current) - AF electrical remodeling support - Reference: Courtemanche et al. (1998) Am J Physiol 5. Windkessel Hemodynamics Models (310 LOC) - 2-element (Frank 1899) - 3-element (Westerhof 1971) - 4-element with inertance (Stergiopulos 1999) - Arterial pressure-flow dynamics - Coupling to cardiac output - References: Frank (1899), Westerhof et al. (2009) Repository Integration Guide (docs/REPOSITORY_INTEGRATIONS.md): Comprehensive documentation linking Multi-Heart-Model to: Surgical Robotics Platforms: - dVRK (da Vinci Research Kit) - Johns Hopkins - CRTK (Collaborative Robotics Toolkit) - AMBF (Asynchronous Multi-Body Framework) - WPI - Surgical Robotics AI - GitHub organization - ROS Medical Robotics - ROS-Med community Cardiac Modeling Platforms: - OpenCARP - Cardiac electrophysiology simulator - Chaste - Computational biology framework - CellML - Model repository and format - CiPA - FDA/EMA drug safety initiative - PhysioNet - Physiological data repository Integration paths: - CellML export/import for model exchange - OpenCARP tissue simulations with Multi-Heart-Model cells - Chaste validation and cross-platform testing - PhysioNet data for parameter estimation - Surgical robot + physiological monitoring workflows Module Updates: src/cardiac/__init__.py: - Export all 5 new models - Comprehensive module documentation - Standard interface documentation README.md: - Move completed models from "Planned" to "Completed" - Update roadmap with new integrations - Add CellML/OpenCARP to planned features Key Features: Electrophysiology Models: ✅ Van der Pol (existing) ✅ Luo-Rudy Dynamic (1994) ✅ Ten Tusscher-Panfilov (2006) ✅ O'Hara-Rudy (2011) - CiPA standard ✅ Courtemanche (1998) - Atrial Hemodynamics Models: ✅ Windkessel 2-element ✅ Windkessel 3-element ✅ Windkessel 4-element with inertance All models follow standard interface: - get_initial_state() -> initial conditions - derivatives(t, state, stimulus) -> state derivatives - step(t, state, dt, stimulus) -> next state via forward Euler Clinical Applications: 1. Drug Safety Testing: - O'Hara-Rudy model for CiPA protocols - QT prolongation assessment - Proarrhythmia prediction 2. Arrhythmia Studies: - Ten Tusscher for ventricular arrhythmias - Courtemanche for atrial fibrillation - Rate-dependent dynamics 3. Hemodynamic Analysis: - Windkessel for arterial compliance - Pressure-flow relationships - Cardiac output coupling 4. Surgical Robotics: - Physiological feedback control - Adaptive robot parameters - Safety constraint enforcement Platform Compatibility: ✅ CellML format (export ready) ✅ OpenCARP integration (documented) ✅ Chaste validation (cross-reference) ✅ PhysioNet data (parameter estimation) ✅ CiPA protocols (ORd model) References: - Luo & Rudy (1994) Circ Res 74(6):1071-1096 - ten Tusscher & Panfilov (2006) Am J Physiol 291(3):H1088-H1100 - O'Hara et al. (2011) PLoS Comput Biol 7(5):e1002061 - Courtemanche et al. (1998) Am J Physiol 275(1):H301-H321 - Westerhof et al. (2009) Med Biol Eng Comput 47(2):131-141 This completes the cardiac model suite from the roadmap and provides comprehensive integration paths with major cardiac modeling and surgical robotics platforms.
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