Status: Planned research and education. Models will use public, de-identified, or synthetic data and will not be presented as clinical tools or patient-specific medical advice.
Human simulation is a stack, not one program
A credible human-body simulation program must distinguish anatomy, tissue mechanics, movement, blood flow, physiology, devices, and clinical workflow. Each layer requires different validation evidence and software.
| Layer | Questions | Initial tools |
|---|---|---|
| Anatomy and medical imaging | How can CT/MRI-derived structures be segmented, registered, visualized, and converted into usable geometry? | 3D Slicer |
| Musculoskeletal biomechanics | How do motion, muscles, joints, and external loads produce forces and movement? | OpenSim |
| Soft tissue and surgical interaction | How do deformable organs and tissues respond to loading, contact, instruments, and cutting? | SOFA |
| Biomechanical finite elements | How do bone, cartilage, ligaments, implants, and tissue structures deform or fail? | FEBio |
| Cardiovascular flow | How do anatomy, boundary conditions, stenosis, aneurysm, and devices affect blood flow and wall mechanics? | SimVascular |
| Physiology | How do coupled biological variables evolve across time and respond to interventions? | OpenCOR / CellML |
| Medical devices and human factors | How do devices interact with anatomy, physiology, operators, alarms, and clinical workflow? | Python, CAD/FEA, discrete-event models |
Project sequence
- Segment a public anatomical dataset and document geometry quality in 3D Slicer.
- Run an OpenSim gait or joint-loading study and compare outputs with published benchmarks.
- Model a simple deformable tissue or instrument-contact problem in SOFA.
- Complete a verified FEBio biomechanics example before creating original anatomy.
- Run a benchmark cardiovascular model in SimVascular and examine boundary-condition sensitivity.
- Simulate a documented physiological model in OpenCOR and reproduce reference behavior.
- Design a medical-device or surgical-system study that combines anatomy, physics, controls, and human factors.
- Develop a validated digital-human or patient-system concept only after the component models are understood.
Failure, safety, and predictive maintenance
This track will examine not only anatomy but also device failure, sensor error, model uncertainty, alarm performance, operator response, implant degradation, equipment maintenance, and the difference between biological variability and system malfunction.
Validation standard
- Begin with published benchmark or tutorial models.
- Separate educational models from clinically validated models.
- Document data provenance, assumptions, boundary conditions, mesh quality, solver behavior, and uncertainty.
- Compare results against analytical solutions, experimental data, published studies, or accepted reference models.
- Never imply diagnostic, treatment, or patient-specific accuracy without appropriate evidence and governance.