An adaptive neuro-fuzzy method ( ANFIS) for estimating single-trial movement-related potentials

Abstract. This study aims to recover transient, trialvarying evoked potentials (EPs), in particular the movement-related potentials (MRPs), embedded within the background cerebral activity at very low signal-to-noise ratios (SNRs). A new adaptive neuro-fuzzy technique will attempt to estimate movement-related potentials within multi-channel EEG recordings, enabling this method to completely adapt to each input sweep without system training procedures. We assume that one of the sensors is corrupted by noise deriving from other sensors via an unknown function that will be estimated. We will approach this problem by: (1) spatially decorrelating the sensors in the preprocessing phase, (2) choosing the most informative of the filtered channels that will permit the best MRP estimation (input-selection phase) and (3) training the neuro-fuzzy model to fit the noise over the chosen sensor and therefore estimating the buried MRP. We tested this framework with simulations to validate the analytic...

• Type: Journal
• Year: 2004
• Where: BC
• Authors: D. D. Ben Dayan Rubin, G. Baselli, Gideon F. Inbar, Sergio Cerutti
• Keywords: Adaptive Neuro-fuzzy Technique, BC 2004, Movement-related Potentials, Sensor