Hyfydy is a musculoskeletal simulation engine that is optimized to run at high simulation frequencies (>3000Hz). This allows for a force-based algorithm for articulated body dynamics that mimics the effect of ligaments and cartilage. Hyfydy effectively utilizes the computational power of modern hardware, resulting in a 50-100x speed gain over OpenSim  — while using the same muscle and contact models. Hyfydy can perform a reflex-based gait simulation  in approximately 80x real-time (Intel i7 CPU, single-core performance).
Hyfydy contains optimized implementations of various Hill-type musculotendon actuators, including the Millard Equilibrium Muscle Model . This model incorporates tendon elasticity and passive damping of the contractile element, allowing muscles to be fully deactivated. Hyfydy also includes several other actuator models, such as rigid tendon muscle actuators and joint torque actuators.
Hyfydy supports a wide range of force-based contact models, including the Hunt-Crossley Contact Model  with non-linear damping. These models better represent soft-tissue contact forces than rigid contact models. The error-controlled integrator with adaptive time steps ensures that the simulation stiffness associated with force-based contact models has a minimal impact on performance.
Accuracy & Stability
Hyfydy faithfully implements muscle and contact models from scientific literature and does not sacrifice accuracy for performance. It supports a number of error-controlled integrators with adaptive step sizes and user-controlled accuracy. This ensures that simulations in Hyfydy always remains stable and accurate, while retaining optimal performance.
Hyfydy is continuously being improved and new features are added regularly based on user requests. It is currently available as a plug-in for SCONE , which is Open Source Software for predictive simulations of biological motion. For questions about a specific feature, please don’t hesitate to send us a message.
* Performance benchmark details: 10 second gait simulation using a reflex-based controller  with hill-type musculotendon dynamics  and non-linear contact forces . Optimizations were performed in SCONE  using 1000 generations of CMA-ES  on a 4-core i7 Intel CPU.
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