发明名称 Method and a system for classifying neural signals, and a method of selecting electrodes for direct neural control
摘要 A classification method for classifying neural signals, the method comprising the following steps: a) using a plurality of electrodes over a determined period of time to acquire a plurality of neural signal samples;b) estimating a covariance matrix of said neural signals; andc) classifying said neural signals, the classification being performed: either in the Riemann manifold of symmetric positive definite matrices of dimensions equal to the dimensions of said covariance matrix;or else in a tangent space of said Riemann manifold.;A method of selecting neural signal acquisition electrodes based on the Riemann geometry of covariance matrices of said signals. An application of said classification method and of said method of selecting electrodes to direct neural control.
申请公布号 US8880163(B2) 申请公布日期 2014.11.04
申请号 US201113180739 申请日期 2011.07.12
申请人 Commissariat a l'Energie Atomique et aux Energies Alternatives 发明人 Barachant Alexandre;Bonnet Stéphane
分类号 A61B5/04;A61B5/00;A61B5/0476;G06K9/00;G06K9/62;G06F3/01 主分类号 A61B5/04
代理机构 Alston & Bird LLP 代理人 Alston & Bird LLP
主权项 1. A classification method for classifying neural signals, the method comprising the following steps: a) acquiring a plurality of neural signal samples (x1(t)-x16(t)) over a determined period of time using a plurality of electrodes (EL1-EL16); and using a data processor device: b) estimating a covariance matrix (Pi) of said neural signals associated with the determined period of time and considered as a point of the Riemann manifold of symmetric positive definite matrices of dimensions equal to the dimensions of said covariance matrix; and c) classifying said neural signals, the classification being performed: either in the Riemann manifold of symmetric positive definite matrices of dimensions equal to the dimensions of said covariance matrix;or else in a tangent space of said Riemann manifold.
地址 Paris FR