article · The Journal of Open Source Software
Biomechanics bridges mechanics, human physiology, and robotics, generating complex datasets that combine skin marker trajectories, contact forces, electromyography signals, and inertial measurement unit kinematics. Integrating these diverse data streams presents a substantial challenge. The biorbd library addresses this integration by focusing on rigid body dynamics and musculoskeletal modelling. Developed as a feature-based library available in C++, Python, and MATLAB, biorbd provides tools to manipulate and analyse biomechanical data in a structured and accessible manner. For any specified musculoskeletal model, the software executes both inverse flow, moving from marker trajectories to muscle activation signals, and direct flow, predicting movement markers from electromyography inputs. Through these functions, the library standardises the simulation and analysis of human body motion across multiple computational environments.
Analysing human movement requires coordinating disparate measurements like muscle activity and body kinematics. By integrating these different data streams within a unified framework, the tool simplifies complex musculoskeletal simulations. This allows specialists in mechanics, physiology, and robotics to study human motion and physical function more effectively using widely adopted programming languages.
The library provides software functionality for developers and researchers working on movement tracking, ergonomics, or rehabilitation systems. By supporting both direct and inverse musculoskeletal calculations across C++, Python, and MATLAB, it enables the processing of complex biomechanical inputs. As a published development library, it represents an applied and functional software tool ready for integration into broader commercial or clinical analytical pipelines.
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Biomechanics is at the interface of several fields of science, such as mechanics, human physiology and robotics. Although this transdisciplinarity encourages the emergence of new ideas, the variety of data to analyze simultaneously can be overwhelming. Commonly biomechanical datasets are composed of skin markers trajectories (termed as markers), contact forces, electromyography (EMG) signal, inertial measurement units (IMU) kinematics, etc., which by nature are not straightforward to combine. It is at their meeting point-the body movementthat biorbd steps in; bio standing for biomechanics and rbd for rigid body dynamics. biorbd is a feature-based development library that targets the manipulation of biomechanical data in a comprehensive and accessible manner. For a given musculoskeletal model, it provides functions for inverse flow-i.e., from markers to EMG-and direct flow-i.e., from EMG to markers.
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DOI: 10.21105/joss.02562
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