The body segment parameters (BSP) of a human body are critical information for modeling, simulating, and understanding human dynamics. The determination of BSPs of human bodies has received increasing attention in biomechanics, sport science, ergonomics, rehabilitation and other fields. This paper presents a momentum-based identification algorithm for dynamically estimating the BSPs of a human body. The human body is modeled as a multibody dynamical system, and the momentum equation of the system can be derived by applying the principle of impulse and momentum. It is possible to formulate the momentum equations corresponding to a set of experiment tests into a linear regression form with respect to the unknown BSPs, which then can be solved using the least square method or other methods. The momentum-based algorithm requires inputting position, velocity, and external force data only. Since acceleration and all the internal force data is not needed, the algorithm is less demanding on measurements and is also less sensitive to measurement errors. As a result, it is practically more appealing than the algorithms depending on the equations of motion. The paper presents the momentum-based inertia identification algorithm along with a simulation study of the algorithm using a simplified trunk-leg model representing a main portion of a human body.

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