Cuff electrode recording has been proposed as a solution to obtain robust feedback signals for closed-loop controlled functional neuromuscular stimulation (FNS) systems. However, single-channel cuff electrode recording requires several electrodes to obtain the feedback signal related to each muscle. In this study, we propose an ankle-angle estimation method in which recording is conducted from the proximal nerve trunk with a multichannel cuff electrode to minimize cuff electrode usage. In experiments, muscle afferent signals were recorded from a rabbit's proximal sciatic nerve trunk using a multichannel cuff electrode, and blind source separation and ankle-angle estimation were performed using fast independent component analysis (PP/FastICA) combined with dynamically driven recurrent neural network (DDRNN). The experimental results indicate that the proposed method has high ankle-angle estimation accuracy for both situations when the ankle motion is generated by position servo system or neuromuscular stimulation. Furthermore, the results confirm that the proposed method is applicable to closed-loop FNS systems to control limb motion.