diff --git a/text/TODO.txt b/text/TODO.txt index 103bf79..5ce9ceb 100644 --- a/text/TODO.txt +++ b/text/TODO.txt @@ -5,6 +5,7 @@ pBurgOrder bestimmen Matching Bewegung EEG + - Passt nicht zusammen - insgesamt ~40s zu wenig kin - durch ridge-Regression (EEG als feature) diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m index 95c2196..912372d 100644 --- a/usedMcode/callAll.m +++ b/usedMcode/callAll.m @@ -31,7 +31,7 @@ subject=subjects{i}; for number=numbers{i} % fprintf('%s%i\n',subject,number); - readEEGEciton(pathToFile,subject,number,windowEMG,windowEEG,shift,5,7500,pburgOrder,minEEGFreq,maxEEGFreq); + readEEG(pathToFile,subject,number,windowEMG,windowEEG,shift,5,7500,pburgOrder,minEEGFreq,maxEEGFreq); meanAccurancysEMG(j)=svmEciton(subject,number,false,k,maxExpC,maxPerClass); meanAccurancysEEG(j)=svmEciton(subject,number,EEG,k,maxExpC,maxPerClass); j=j+1; diff --git a/usedMcode/generateTrainingData.m b/usedMcode/generateTrainingData.m index f62bd88..d188438 100644 --- a/usedMcode/generateTrainingData.m +++ b/usedMcode/generateTrainingData.m @@ -21,5 +21,5 @@ end trainingDataEMG=permute(tempEMG,[2 1 3]); - kinPerSec=shiftingKin(kin,frequency,windowEEG,shift); + kinPerSec=shiftingKin(kin,windowEEG,shift); end diff --git a/usedMcode/namesAndNumbers.m b/usedMcode/namesAndNumbers.m index 877ef27..cedd10a 100644 --- a/usedMcode/namesAndNumbers.m +++ b/usedMcode/namesAndNumbers.m @@ -1,5 +1,5 @@ function [names,numbers]=namesAndNumbers(pathToFile) - fileID=fopen(strcat(pathToFile,'dirs,txt'); + fileID=fopen(strcat(pathToFile,'dirs.txt')); text=textscan(fileID,'%s','Delimiter','\n'); text=text{1}; j=0; diff --git a/usedMcode/readEEG.m b/usedMcode/readEEG.m index 142dea6..1dab896 100644 --- a/usedMcode/readEEG.m +++ b/usedMcode/readEEG.m @@ -15,32 +15,32 @@ %fprintf('%ith file processed\n',i) end - clear sig + %clear sig trainingDataEEG=cell2mat(trainingDataEEGcell); trainingDataEMG=cell2mat(trainingDataEMGcell); classesMat=cell2mat(classesCell); kinMat=cell2mat(kin); - clear trainingDataEEGcell trainingDataEMGcell classesCell kin + %clear trainingDataEEGcell trainingDataEMGcell classesCell kin classificationWithPause=classifyAccordingToEMG(trainingDataEEG, trainingDataEMG,classesMat,shift,params.SamplingRate.NumericValue,threshold); - clear classesMat + %clear classesMat smoothClassification=zeros(size(classificationWithPause)); for i=1:size(classificationWithPause,1) smoothClassification(i)=round(mode(classificationWithPause(max(i-2,1):min(i+2,end)))); end - clear classificationWithPause + %clear classificationWithPause trainingDataEEG=trainingDataEEG(smoothClassification~=-1,:,:); trainingDataEMG=trainingDataEMG(smoothClassification~=-1,:); classification=smoothClassification(smoothClassification~=-1); kinematics=kinMat(smoothClassification~=-1,:); - clear smoothClassification i + %clear smoothClassification i save(strcat(pathToFile,sprintf('../matlabData/%s%i200msWindowEMG1sWindowEEG200msShift1sPauseFreq0to200.mat',subject,number)),'trainingDataEEG','trainingDataEMG','classification','kinematics','-v7.3'); - %fprintf('end read %s%i %s\n',subject,number,datestr(datetime('now'))); + %fprintf('finished reading %s%i %s\n',subject,number,datestr(datetime('now'))); end diff --git a/usedMcode/shiftingKin.m b/usedMcode/shiftingKin.m index 4130c76..2a62296 100644 --- a/usedMcode/shiftingKin.m +++ b/usedMcode/shiftingKin.m @@ -1,6 +1,6 @@ function [kinPerSec]=shiftingKin(kin, window, shift) kinPerSec=zeros(fix((max(kin(:,1))-window*1000)/(shift*1000)),3); for j=1:fix((max(kin(:,1))-window*1000)/(shift*1000)) - kinPerSec(j,:)=sum(diff(kin(kin(:,1)>=(j-1)*shift*1000 & kin(:,1)<=(j-1)*shift*1000+window*1000,2:4))); + kinPerSec(j,:)=sum(diff(kin(kin(:,1)>(j-1)*shift*1000 & kin(:,1)<=(j-1)*shift*1000+window*1000,2:4))); end end \ No newline at end of file