The human body is modeled as a humanoid robot with 34 dof and 15 links. The inverse dynamic model of the robot is linear in relation to 10 standard physical inertial parameters for each link which are the mass, the 6 inertia matrix coefficients and the 3 center of mass coordinates. For robotics control or simulation applications, a minimum number of b base parameters, b < 150, can be identified by linear LS techniques using motion capture and foot/ground contact force/torque data measurements. But some base parameters are not well identified due to measuring errors and poor excitation. They have no statistical significant values and they can lose their physical meaning. Because these parameters have little contribution in the measured force/torque they can be eliminated from the model to calculate a subset of significant base parameters called the essential parameters [1], [2], [3]. For medical applications the physical anatomical meaningful values are needed for the 150 standard parameters of the 15 segments of the human body model, not only a minimal set of parameters. Based on the essential parameters we propose to calculate the LS solution with SVD factorization, which is the closest in 2 norm of a set of a priori anatomic values given by literature database. This solution keeps both the same minimum norm error given by the essential parameters and the physical anatomical meaning of the a priori values when the measuring noise and errors are small. Experimental results are presented and discussed.