This GIT respository contains all files needed for an adequate analysis of the gait (6MWT) accelerometer data.
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function divergence=div_calc_shorttimeseries(state,ws_sec,fs,period_sec,progress) % calculate local dynamic stability (max lyapunov exponent). % Input: % state: appropriate state space % ws: window size over which divergence should be calculated(in seconds) % fs: sample frequency % period: ..... (can be dominant period in the signal(in seconds)) % plotje: show a graph. % % Note that in this version ws should be larger than 4*period, as the long % term divergence is calculated from 4*period to ws*fs. % % Output: % divergence: the divergence curve % lds: the 2 estimates of the maximum lyapunov exponents (short term and long term) % % Earlier versions by KvS en SMB. Made the routine faster, 14/01/2011, Sietse Rispens % Use less memory to prevent memory error, 01/02/2011, Sietse Rispens % Take mean of the log of divergence instead of log of the mean of divergence, 26/05/2011, Sietse Rispens % Allow non-integer ws_sec and period_sec and change fitting-range, 01/08/2011, Sietse Rispens % Do not try to find neighbours that need to be followed beyond end of time series, 01/11/2012, Sietse Rispens % Exclude neighbours closer than Period in time (instead of period/2), 01/11/2012, Sietse Rispens [m,n]=size(state); ws=round(ws_sec*fs); period=round(period_sec*fs); mcompletewindow = m-ws+1; statecw = state(1:mcompletewindow,:); divergence_sum=zeros(1,ws); divergence_count=zeros(1,ws); diff_state = statecw*0; diff_state_sqr = diff_state; diff_total = zeros(size(diff_state,1),1); for i = 1:mcompletewindow if ~isnan(state(i,:)) start=round(max([1,i-period+1])); stop=round(min([mcompletewindow,i+period-1])); for j=1:n, diff_state(:,j) = statecw(:,j)-statecw(i,j); diff_state_sqr(:,j)=diff_state(:,j).^2; end diff_total(:,1)=sum(diff_state_sqr,2); diff_total(start:stop,1)=NaN; [mini,index]=min(diff_total); if i+ws>m || index+ws>m % do not use these data else divergence_sum = divergence_sum + log(sqrt(sum((state(i:i+ws-1,:)-state(index:index+ws-1,:)).^2,2)))'; divergence_count = divergence_count + 1; end end if progress > 0 if mod(i,round(progress))==0 if i>round(progress) fprintf('\b\b\b\b\b\b\b\b\b\b'); end fprintf('i=%8d', i); end end end if progress > 0 fprintf('\n'); end divergence= (divergence_sum./divergence_count);