COMMISSARIAT A L'ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
发明人:
Andriy YELISYEYEV
申请号：
US16473516
公开号：
US20190320924A1
申请日:
2017.12.22
申请国别(地区):
US
年份:
2019
代理人:
摘要：
The subject of the invention is a method for calibrating a direct neural interface. The calibration is performed by considering a so-called input calibration tensor, formed on the basis of measured electrophysiological signals and so-called output calibration tensor, formed on the basis of measured output signals. The method comprises the application of a least squares multivariate regression implemented by considering a covariance tensor and a cross-covariance tensor which are established on the basis of input and output calibration tensors corresponding to a current calibration period. The method takes into account covariance and cross-covariance tensors established during an earlier calibration period prior to the current calibration period, these tensors being weighted by a forget factor.
