Dynamic joint stiffness defines the torque generated at the joint in response to position perturbations. Dynamic stiffness is modulated by the angular position and the muscle activation level, making it difficult to estimate during large movements and/or time-varying muscle contractions. This paper presents a new methodology for estimating dynamic joint stiffness during movement and muscle activation. For this, we formulate a novel, nonlinear, dynamic joint stiffness model and present a new algorithm to estimate its parameters. The algorithm assumes that the variability in the model parameters is a function of the mean joint position. Using this methodology we estimated the dynamic joint stiffness at the ankle throughout ramp and hold displacements during a constant muscle contraction. The estimated model accurately predicted the intrinsic and reflex torques produced at the ankle as a response to small position perturbations during large displacement with muscle activation. Preliminary results show that during muscle contraction, ankle intrinsic stiffness estimated during movement is significantly lower than that estimated during quasi-stationary experiments.