When the hand is displaced from the equilibrium posture by an external disturbance, a force is generated to restore the original position and there is ample evidence that humans are able to control the endpoint impedance of their arms in response to active destabilizing force fields. Goal of this thesis is to extract the impedance information of human arm when the arm is in the particular posture and while moving on a particular trajectory. In this work two models of the arm, Joint Space Model and Muscle Space Model, are considered while major emphasize is given to Muscle Space Model. The musculoskeletal model describes planar movements of the upper arm and forearm, which are moved by eight lumped muscles with nonlinear dynamics. A non-linear Hunt-Crossley model is considered for muscles model which is the function of the velocity of the shortening or lengthening, muscle length at that instance and also on the viscoelastic parameters of the corresponding muscle. End-point impedance is estimated by simulating a given model, by transforming a muscle force to joint torque and then to endpoint impedance, which is generated due to a particular movement or while maintaining a particular arm posture. The dynamics at the endpoint level are estimated so that a comparison can be made with the experiments. The resulted impedance parameter helps to design the control of robots and human machine interface.