Robot manipulators have the capability to exceed human ability in one particular area; strength. The human's ability to perform a variety of physical tasks is limited not by his intelligence, but by his physical strength. If we can more closely integrate the mechanical power of a machine with human hand under the supervisory control of the human's intellect, we will then have a system which is superior to a loosely-integrated combination of a human and his fully automated robot as in the present day robotic systems. We must therefore develop a fundamental approach to the problem of this "extending" human mechanical power in certain environments. The work presented here defines "Extenders" as a class of robot manipulators worn by humans to increase human mechanical strength, while the wearer's intellect remains the central intelligent control system for manipulating the extender. The human body, in physical contact with the extender, exchanges information signals and power with the extender. This paper focuses on the issues related to the dynamics and control of human machine interaction in the sense of the transfer power and information signals. General models for the human, the extender and the interaction between the human and the extender have been developed. Unstructured modeling was chosen in order to include all the dynamics in the systems, to avoid specific models. The Small Gain Theorem and the Nyquist Criterion (frequency domain) for the linearly treated systems have been used for the stability analysis of human machine interaction.