28 lines
1019 B
Matlab
28 lines
1019 B
Matlab
% Function for calculating multiscale entropy
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% input: signal
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% m: match point(s)
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% r: matching tolerance
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% factor: number of scale factor
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% sampenc is available at http://people.ece.cornell.edu/land/PROJECTS/Complexity/sampenc.m
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%
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% Multi-scale sample Entropy (Mscale-En) is an indicator of gait predictability. Multi-scale entropy takes the
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% complexity of a system into account by calculating the
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% predictability of a signal over time scales with increasing
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% length. A ‘coarse-graining’ process is applied to the acceleration signals; non-overlapping windows of data
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% points with an increasing length τ are constructed, with
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% τ representing the time scale with a tolerance of r (in the
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% present study τ = 7 and r = 0.2). A complete predictable
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% signal will adopt a Mscale-En value of 0 [29].
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function e = msentropy(input,m,r,factor)
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y=input;
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y=y-mean(y);
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y=y/std(y);
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for i=1:factor
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s=coarsegraining(y,i); % dont have this function yet.
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sampe=sampenc(s,m+1,r);
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e(i)=sampe(m+1);
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end
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e=e'; |