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People usually develop different kinds of compensated gait in response to their local function deficits, such as muscle weakness, spasticity in specific muscle groups, or joint stiffness, to overcome the risk of falling-down. Compensated walking in impaired walking has been analyzed empirically in gait analysis area. However, the characteristic of the compensated walking has not been analyzed considering the nervous system. In this research, we employed a bio-mimetic humanoid robot with a neural model to emulate a hemiplegic gait with a deficit in the ankle flexor and the hip extensor. The deficits were expressed by setting a limitation for the outputs of the ankle flexor and decreasing the output of the hip extensor. Then a compensatory mechanism was explored by adjusting the outputs of the other muscles. We showed that, it is possible to use this approach to quantitatively analyze a hemiplegic gait and its compensated walking. Thus, in this research we were able to improve the behavioral understanding of a compensated gait and bring insights that will help build useful walking assistive systems or for designing effective rehabilitation therapies.