Wasim Qamar Malik,Leigh Robert Hochberg,Emery Neal Brown
申请号：
US15549358
公开号：
US20180039328A1
申请日:
2015.04.21
申请国别(地区):
US
年份:
2018
代理人:
摘要：
Computationally efficient procedure for estimating modulation depth from multivariate data. Neural interface system utilizing such procedure to rank neural signals and select optimal channel subset for inclusion in the neural decoding algorithm. The proposed system offers several orders of magnitude lower complexity and data-processing time but virtually identical decoding performance compared to greedy search and other selection schemes and is applicable to wide variety of problems involving multisensor signal modeling and estimation in biomedical engineering systems. The use of the system to the modulation depth of human motor cortical function shows that single-unit signals are characterized by the generalized Pareto distribution.
