Patent ID: 8433663
Filing Date: 2013-04-30
Classification: G06K,G06N

Abstract:
1. Process for the computerized prevision of intended movements (X) from neuronal signals (Y) of a proband's brain, wherein the neuronal signals (Y) are associated each time with intended movements (X) in the brain, wherein the most likely movements (X) are determined based on detected neuronal signals (Y), namely using at least one model, wherein the at least one model describes a mapping (H) of neuronal signals (Y) on the possible intended movements (X), wherein the process comprises: wherein the at least one model (H) is determined each time by at least one characteristic and the at least one characteristic of the at least one model is updated in the updating step, wherein the at least one model (H) is an adaptive model (p(Y|X)) of Gauss distributed probabilities for a predetermined number, K, of classes of movements (X), wherein the at least one model comprises the average (mu_k) with k={1, . . . , K} as well as the covariance matrix (C_k) of the Gauss distribution as at least one characteristic, and in wherein the average (mu_k) of the predetermined classes of movement (X_ wherein the following applies for each of the probabilities p(X for the averages the following applies: and the following applies for the covariance: