Abstract: An equivalent experimental platform for a 3 DOF (degree of freedom) micromanipulator is established to solve the force sensing problem for surgical robot micromanipulator. A comprehensive resistance model of the driven joint unit is designed based on the complete dynamic models of the cable-driven micromanipulator joints, and the comprehensive resistance neural network model is obtained through data fitting of the experimental results based on BP (backpropagation) neural network model. Finally, a clamping force estimation strategy is proposed based on the comprehensive resistance changes of the driven unit, and its performance is verified by the experiments of continuous and stepped clamping force loading. The experiment results show that the maximum absolute error is 0.24 N in clamping force measurement, and the accuracy can reach up to 90% in stable period. The method lays the foundation for realizing force feedback of the surgical robot micromanipulator.