Proposition, identification, and experimental evaluation of an inverse dynamic neuromusculoskeletal model for the human finger

•We propose an inverse dynamic neuromusculosketal model for the middle finger during motion.•The optimization problem for estimating the model unknowns is complex.•We propose a multistep robust estimation procedure to solve this problem.•We test it by simulation and propose an attempt to experimentally evaluate the proposed model.•The proposed model should be useful for rehabilitation applications.

PurposeThe purpose of this study is to develop an inverse dynamic model of the human middle finger in order to identify the muscle activation, muscle force, and neural activation of the muscles involved during motion. Its originality comes from the coupling of biomechanical and physiological models and the proposition of a dedicated optimization procedure and cost function for identifying the model unknowns.MethodsThree sub-models work in interaction: the first is the biomechanical model, primarily consisting of the dynamic equations of the middle finger system; the second is the muscle model, which helps to identify the muscle force from muscle activation and dynamic deformation for six involved muscles. The third model allows one to link muscle activation to neural intent from the Central Nervous System (CNS). This modeling procedure leads to a complex analytical nonlinear system identified using multi-step energy minimization procedure and a specific cost function.ResultsNumerical simulations with different articulation velocities are presented and discussed. Then, experimental evaluation of the proposed model is performed following a protocol combining electromyography and motion capture during a hand opening–closing paradigm. After comparison, several results from the simulation and experiments were found to be in accordance. The difficulty in evaluating such complex dynamic models is also demonstrated.ConclusionsDespite the model simplifications, the obtained preliminary results are promising. Indeed, the proposed model, once correctly validated in future works, should be a relevant tool to simulate and predict deficiencies of the middle finger system for rehabilitation purposes.