A method for determining the functional topography of a peripheral nerve of a user comprising the steps of prearranging an electrode comprising a number n of channels ci, with i = 1,2..., n, arranging the electrode in such a way that each channel is in contact with the peripheral nerve at a respective contact point pi, with i = 1,2..., n, generating a model of a cross section S of the peripheral nerve where the area A of the cross section S comprises a number m of areas αj, with j = 1,2,..., m, computing a lead field matrix L = [Rj,i], wherein Rj,i is a value that describes the electrostatic relationship between an area αj and a contact point pi of the cross section S, periodic acquisition, by the electrode, of a number n of voltage values Vki at instants tk, with k = 1,2,...,S, obtaining a voltage matrix V = [Vk,i], with i = 1,2,...,n, where Vki is the voltage value determined by the channel ci at the contact point pi at the instant tk, periodic acquisition, by at least one medical device, of a number r of values of physiological signals Pk,h of the user at instants tk, with k = 1,2,..., s, obtaining a matrix of the physiological signals P = [Pk,h], with h. = 1,2,...,r, where Pk k is the value of the h-th physiological signal determined at the instant tk, computing a discrimination matrix = D = [dh,i], D being function of the matrices V = [Vk,i] and P = [Pk,h], where dh,i is the discrimination coefficient which represents the correlation between the h-th physiological signal Pk,h and the i-th voltage value Vk,i referred to a same instant tk, computing a spatial filtering matrix ΦDBF= [φh,j], φh,j being the localization index which represents the correlation between the h-th physiological signal and the area αj of said cross section S, generating a functional topography of said peripheral nerve, for each h-th physiological signal, wherein each area αj is graphically identified as a function of the corresponding value φh,j associated with it by the spatial filtering matrix ΦDBF .
Method for determining the functional topography of a peripheral nerve
Andrea PitzusPrimo
;
2023-01-01
Abstract
A method for determining the functional topography of a peripheral nerve of a user comprising the steps of prearranging an electrode comprising a number n of channels ci, with i = 1,2..., n, arranging the electrode in such a way that each channel is in contact with the peripheral nerve at a respective contact point pi, with i = 1,2..., n, generating a model of a cross section S of the peripheral nerve where the area A of the cross section S comprises a number m of areas αj, with j = 1,2,..., m, computing a lead field matrix L = [Rj,i], wherein Rj,i is a value that describes the electrostatic relationship between an area αj and a contact point pi of the cross section S, periodic acquisition, by the electrode, of a number n of voltage values Vki at instants tk, with k = 1,2,...,S, obtaining a voltage matrix V = [Vk,i], with i = 1,2,...,n, where Vki is the voltage value determined by the channel ci at the contact point pi at the instant tk, periodic acquisition, by at least one medical device, of a number r of values of physiological signals Pk,h of the user at instants tk, with k = 1,2,..., s, obtaining a matrix of the physiological signals P = [Pk,h], with h. = 1,2,...,r, where Pk k is the value of the h-th physiological signal determined at the instant tk, computing a discrimination matrix = D = [dh,i], D being function of the matrices V = [Vk,i] and P = [Pk,h], where dh,i is the discrimination coefficient which represents the correlation between the h-th physiological signal Pk,h and the i-th voltage value Vk,i referred to a same instant tk, computing a spatial filtering matrix ΦDBF= [φh,j], φh,j being the localization index which represents the correlation between the h-th physiological signal and the area αj of said cross section S, generating a functional topography of said peripheral nerve, for each h-th physiological signal, wherein each area αj is graphically identified as a function of the corresponding value φh,j associated with it by the spatial filtering matrix ΦDBF .
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