This project focuses on using OpenSim musculoskeletal models to analyze human limb movement, with an emphasis on either the upper or lower limb. The project begins by selecting an appropriate OpenSim model, describing its joint degrees of freedom, range of motion, and the muscles involved.

Data is then collected for the selected limb's movement, either from community datasets or through custom data collection using lab facilities. This data is represented in the report with relevant plots and explanations.

Inverse kinematics and dynamics are performed in OpenSim to compute joint angles and torques for the selected movement, with the results explained and plotted. Additionally, the OpenSim computed muscle control algorithm is applied to estimate the muscle forces required to execute the motion. The muscle recruitment solution is analyzed, identifying which muscles are activated, when they are actuated, and the level of activation.

A sensitivity analysis is conducted to assess the impact of changes to the model, such as adding or removing muscles or altering the mass of limb segments. The project concludes with comments on the optimization problem that OpenSim uses to determine muscle recruitment, discussing its relevance and applicability to the limb movement under study.

This comprehensive project will contribute to a better understanding of human-robot interaction by investigating how human limbs move and the forces required to perform specific motions.