Estimating model parameters of a mathematical model for hand motion during cylindrical grasps

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This paper presents parameter estimation for the passive moment and musculoskeletal scaling coefficients of a mathematical model describing the equations of motion of human finger segments. A novel musculoskeletal model was used as the actuator and parameter estimation was performed by least squares optimization of the differences between angular data from a motion capture system, and the solutions to the equations of motion of our model. The parameter estimates determined are unique to the individual and the dataset. Model fits show good agreement with filtered data R2= 0.98. The hope is that this model and approach can be used to determine the passive moment and musculoskeletal scaling coefficients for all types of grasps.