The ability to recover signals from the peripheral nerves would provide natural and physiological signals for controlling artificial limbs and neural prosthetic devices. Current cuff electrode systems can provide multiple channels but the signals have low signal to noise ratio and are difficult to recover. Previous work has shown that beamforming algorithms provide a method to extract such signals from peripheral nerve activiy [1]. This paper describes in-silico and in vivo experiments done to validate that method in a more realistic case. A modified beam forming algorithm capable of significantly decrease cross talk between channels is described and the results of the a 16-channel Flat Interface Nerve Electrode used to recover signals from the sciatic nerve in rabbit while the distal tibial and peroneal branches were stimulated The beamforming spatial filters were able to distinguish which branch was being stimulated, and in many cases how strongly, over a large range of stimulation intensities.