Open AccessImproving the analysis of near-infrared spectroscopy data with multivariate classification of hemodynamic patterns: a theoretical formulation and validation
Author(s) -
Jessica Gemignani,
E. Middell,
Randall L. Barbour,
Harry L. Graber,
Benjamin Blankertz
Publication year - 2018
Publication title -
journal of neural engineering
Language(s) - English
Resource type - Journals
eISSN - 1741-2560
pISSN - 1741-2552
DOI - 10.1088/1741-2552/aabb7c
Subject(s) - linear discriminant analysis , multivariate statistics , general linear model , pattern recognition (psychology) , artificial intelligence , computer science , classifier (uml) , multivariate analysis , linear classifier , linear model , a priori and a posteriori , statistics , machine learning , mathematics , epistemology , philosophy
The results obtained suggest that the outcome of GLM analysis is highly vulnerable to violations of theoretical assumptions, and that therefore a data-driven approach such as that provided by the proposed LDA-based method is to be favored.
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