Modeling study of peripheral nerve recording selectivity.
Recording of sensory information from afferent fibers can be used as feedback for the closed-loop control of neural prostheses. Clinical applications suggest that recording selectively from various nerve fascicles is important. Current nerve cuff electrodes are generally circular in shape and use a tripolar recording configuration. Preliminary experiments suggest that slowly changing the shape of the nerve to a flatter cross section can improve its selectivity. The objective of this work is to determine the effects of nerve reshaping and other cuff design parameters on the fascicular recording selectivity of a nerve cuff. A finite-element computer model of a multifasciculated nerve with different cuff electrodes was implemented to simulate the recordings. The model included the inhomogeneous and anisotropic properties of peripheral nerves. The recording selectivity was quantified with the use of a Selectivity Index. The results from the model provided information regarding the effect of using monopolar versus tripolar recording configurations, the length of the tripoles in tripolar recordings, the number of contacts that maximize the selectivity index, and the cuff length. Nerve reshaping was found to cause important recording selectivity improvements (106% average). These results provide specific criteria for the design of selectively recording nerve cuff electrodes.
Perez-Orive
J
J
Neural Engineering Center, Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Durand
D M
DM
D000344:Afferent Pathways / Q000503:physiopathology*; D016880:Anisotropy; D001186:Artificial Limbs; D004599:Electric Stimulation Therapy / Q000295:instrumentation / Q000379:methods; D004567:Electrodes, Implanted; D004576:Electromyography / Q000295:instrumentation / Q000379:methods; D004867:Equipment Design; D005246:Feedback; D020342:Finite Element Analysis; D006801:Humans; D008959:Models, Neurological; D010525:Peripheral Nerves / Q000473:pathology* / Q000503:physiopathology*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation