Comparing Different Methods to Create a Linear Model for Uncontrolled Manifold Analysis
Author(s) -
Inge Tuitert,
Tim A. Valk,
Egbert Otten,
Laura Golenia,
Raoul M. Bongers
Publication year - 2018
Publication title -
motor control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.514
H-Index - 46
eISSN - 1543-2696
pISSN - 1087-1640
DOI - 10.1123/mc.2017-0061
Subject(s) - linear regression , regression analysis , linear model , proper linear model , mathematics , manifold (fluid mechanics) , regression , joint (building) , relation (database) , position (finance) , statistics , computer science , bayesian multivariate linear regression , data mining , engineering , mechanical engineering , architectural engineering , finance , economics
An essential step in uncontrolled manifold analysis is creating a linear model that relates changes in elemental variables to changes in performance variables. Such linear models are usually created by means of an analytical method. However, a multiple regression analysis is also suggested. Whereas the analytical method includes only averages of joint angles, the regression method uses the distribution of all joint angles. We examined whether the latter model is more suitable to describe manual reaching movements. The relation between estimated and measured fingertip-position deviations from the mean of individual trials, the relation between fingertip variability and nongoal-equivalent variability, goal-equivalent variability, and nongoal-equivalent variability indicated that the linear model created with the regression method gives a more accurate description of the reaching data. Therefore, we suggest the usage of the regression method to create the linear model for uncontrolled manifold analysis in tasks that require the approximation of the linear model.
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