This GIT respository contains all files needed for an adequate analysis of the gait (6MWT) accelerometer data.
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 2 years ago function [ResultStruct] = HarmonicityFrequency(dataAccCut_filt,P,F, StrideFrequency,dF,LowFrequentPowerThresholds,N_Harm,FS,AccVectorLen,ResultStruct) % Add sum of power spectra (as a rotation-invariant spectrum) P = [P,sum(P,2)]; PS = sqrt(P); % Calculate the measures for the power per separate dimension for i=1:size(P,2); % Relative cumulative power and frequencies that correspond to these cumulative powers PCumRel = cumsum(P(:,i))/sum(P(:,i)); PSCumRel = cumsum(PS(:,i))/sum(PS(:,i)); FCumRel = F+0.5*dF; % Derive relative cumulative power for threshold frequencies Nfreqs = size(LowFrequentPowerThresholds,2); LowFrequentPercentage(i,1:Nfreqs) = interp1(FCumRel,PCumRel,LowFrequentPowerThresholds)*100; % Calculate relative power of first 10 harmonics, taking the power of each harmonic with a band of + and - 10% of the first % harmonic around it PHarm = zeros(N_Harm,1); PSHarm = zeros(N_Harm,1); for Harm = 1:N_Harm, FHarmRange = (Harm+[-0.1 0.1])*StrideFrequency; PHarm(Harm) = diff(interp1(FCumRel,PCumRel,FHarmRange)); PSHarm(Harm) = diff(interp1(FCumRel,PSCumRel,FHarmRange)); end % Derive index of harmonicity if i == 2 % for ML we expect odd instead of even harmonics IndexHarmonicity(i) = PHarm(1)/sum(PHarm(1:2:12)); elseif i == 4 IndexHarmonicity(i) = sum(PHarm(1:2))/sum(PHarm(1:12)); else IndexHarmonicity(i) = PHarm(2)/sum(PHarm(2:2:12)); end % Calculate the phase speed fluctuations StrideFreqFluctuation = nan(N_Harm,1); StrSamples = round(FS/StrideFrequency); for h=1:N_Harm, CutOffs = [StrideFrequency*(h-(1/3)) , StrideFrequency*(h+(1/3))]/(FS/2); if all(CutOffs<1) % for Stride frequencies above FS/20/2, the highest harmonics are not represented in the power spectrum [b,a] = butter(2,CutOffs); if i==4 % Take the vector length as a rotation-invariant signal AccFilt = filtfilt(b,a,AccVectorLen); else AccFilt = filtfilt(b,a,dataAccCut_filt(:,i)); end Phase = unwrap(angle(hilbert(AccFilt))); SmoothPhase = sgolayfilt(Phase,1,2*(floor(FS/StrideFrequency/2))+1); % This is in fact identical to a boxcar filter with linear extrapolation at the edges StrideFreqFluctuation(h) = std(Phase(1+StrSamples:end,1)-Phase(1:end-StrSamples,1)); end end FrequencyVariability(i) = nansum(StrideFreqFluctuation./(1:N_Harm)'.*PHarm)/nansum(PHarm); if i<4, % Derive harmonic ratio (two variants) if i == 2 % for ML we expect odd instead of even harmonics HarmonicRatio(i) = sum(PSHarm(1:2:end-1))/sum(PSHarm(2:2:end)); % relative to summed 3d spectrum HarmonicRatioP(i) = sum(PHarm(1:2:end-1))/sum(PHarm(2:2:end)); % relative to own spectrum else HarmonicRatio(i) = sum(PSHarm(2:2:end))/sum(PSHarm(1:2:end-1)); HarmonicRatioP(i) = sum(PHarm(2:2:end))/sum(PHarm(1:2:end-1)); end end end ResultStruct.IndexHarmonicity_V = IndexHarmonicity(1); % higher smoother more regular patter ResultStruct.IndexHarmonicity_ML = IndexHarmonicity(2); % higher smoother more regular patter ResultStruct.IndexHarmonicity_AP = IndexHarmonicity(3); % higher smoother more regular patter ResultStruct.IndexHarmonicity_All = IndexHarmonicity(4); ResultStruct.HarmonicRatio_V = HarmonicRatio(1); ResultStruct.HarmonicRatio_ML = HarmonicRatio(2); ResultStruct.HarmonicRatio_AP = HarmonicRatio(3); ResultStruct.HarmonicRatioP_V = HarmonicRatioP(1); ResultStruct.HarmonicRatioP_ML = HarmonicRatioP(2); ResultStruct.HarmonicRatioP_AP = HarmonicRatioP(3); ResultStruct.FrequencyVariability_V = FrequencyVariability(1); ResultStruct.FrequencyVariability_ML = FrequencyVariability(2); ResultStruct.FrequencyVariability_AP = FrequencyVariability(3); ResultStruct.StrideFrequency = StrideFrequency;