Neuro-fuzzy extraction of angular information from muscle afferents for ankle control during standing in paraplegic subjects: An animal model

This paper is part of a project whose aim is the implementation of closed-l oop control of ankle angular position during functional electrical stimulat ion (FES) assisted standing in paraplegic subjects using natural sensory in formation, In this paper, a neural fuzzy (NF) model is implemented to extra ct angular position information from the electroneurographic signals record ed from muscle afferents using cuff electrodes in an animal model. The NF m odel, named dynamic nonsingleton fuzzy logic system is a Mamdani-like fuzzy system, implemented in the framework; of recurrent neural networks, The fu zzification procedure implemented was the nonsingleton technique which has been shown ire previous works to be able to take into account the uncertain ty in the data. The proposed algorithm was tested in different situations a nd was able to predict reasonably well the ankle angular trajectories espec ially for small excursions las during standing) and when the stimulation si tes are far from the registration sites. This suggests it may be possible t o use activity from muscle afferents recorded with cuff electrodes for PES closed-loop control of ankle position during quite standing.