The Pulse Physiology Engine can be used as a standalone library or integrated with simulators, sensor interfaces, and models of all fidelities. The platform includes a common data model for standard model and data definitions, a software interface for engine control, robust physics-based circuit and transport solvers, and a verification and validation suite. The architecture was specifically designed to reduce model development time and increase the usability of the engine in simulations by creating a modular, extensible definition for human physiology. Pulse provides the following benefits to its user community:

• Sound underlying physics: Clear, accurate, precise first principles conservation equations
• Standardized data model: Easily understandable, widely usable, ontologies and software interfaces
• Extensible: Reusable, repeatable implementation to allow the addition of new capabilities and functionality
• Modular: Interdependent, hierarchical models for varying fidelity and complexity
• Thorough documentation: In-depth, referenced descriptions of physiology methodology and software design
• Cross-platform deployment: Easy compilation on all standard operating systems (Windows, Mac, Linux, and ARM) and multiple languages (C++, C#, Java, Python)
• Credible: Computational models transparently derived from evidence-based literature and analyzed with extensive verification and validation tools
• Open: Public repository managed by experienced Kitware team with a permissible Apache 2.0 license for multicenter and multidisciplinary collaborative development

Pulse is comprised of numerical models representing the different body systems, feedback mechanisms and interactions between the systems, PK/PD, and medical equipment. The major systems are modeled using zero-dimensional lumped-parameter circuit analogs (e.g., the cardiovascular circuit) with homeostatic feedback. The differential equations contained in each system are calculated through transient analysis with a shared dynamic time step. The numerical models currently execute with a time step of 20 ms, which can be reduced, as necessary, to ensure all physiology features of interest are captured, while maintaining real-time execution for the simulation.