This GIT respository contains all files needed for an adequate analysis of the gait (6MWT) accelerometer data.
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function minmuttau = findminMutInf(miV,nsam)
% minmuttau = findminMutInf(miV,nsam)
% findminMutInf finds the lag tau of the first local minimum of mutual
% information 'miV' (given from lag 0 and up to a maximum lag 'taumax')
% and using a sliding window of length 2*nsam+1.
%========================================================================
% <findminMutInf.m>, v 1.0 2010/02/11 22:09:14 Kugiumtzis & Tsimpiris
% This is part of the MATS-Toolkit http://eeganalysis.web.auth.gr/
%========================================================================
% Copyright (C) 2010 by Dimitris Kugiumtzis and Alkiviadis Tsimpiris
% <dkugiu@gen.auth.gr>
%========================================================================
% Version: 1.0
% LICENSE:
% This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 3 of the License, or
% any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see http://www.gnu.org/licenses/>.
%=========================================================================
% Reference : D. Kugiumtzis and A. Tsimpiris, "Measures of Analysis of Time Series (MATS):
% A Matlab Toolkit for Computation of Multiple Measures on Time Series Data Bases",
% Journal of Statistical Software, in press, 2010
% Link : http://eeganalysis.web.auth.gr/
%=========================================================================
taumax = length(miV)-1;
minmuttau = NaN;
if taumax>2*nsam
i=nsam+1;
found = 0;
while i<taumax+1-nsam & found==0
winx = miV([i-nsam:i-1 i+1:i+nsam]);
check = find(miV(i) < winx);
if length(check) == length(winx)
found=1;
else
i=i+1;
end
end
if found
minmuttau = i-1;
end
end