有没有一种从知识中检索生理数据并在R中进行预处理的方法？

Question

我正在尝试从Acqknowledge中检索原始的生理数据(手动纳米)，以便能够以自动化的方式对它们进行预处理，并在R(或Matlab)中进行分析。有办法吗？我希望避免在R中手动复制/粘贴数据，从应答到Excel中读取数据。

然后，我想在数据上应用一个过滤器，并检索R中感兴趣的压缩信息，有什么方法可以做到吗？

欢迎您提出任何建议，谢谢！

Answer 1

我也有过类似的问题。关键是load_acq.m函数，您可以在这里找到-> https://github.com/munoztd0/fusy-octave-memories/blob/main/load_acq.m，然后可以循环遍历它们，并将它们保存为.csv或在R中可以加载和使用的任何东西。

至于如何做到这一点，我已经做了一个小例行公事。

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Create physiological files from AcqKnowledge
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% SETTING THE PATH
path = 'your path here'; %your path here
physiodir   = fullfile(path, '/SOURCE/physio');
outdir = fullfile(path, '/DERIVATIVES/physio');
session = "first" %your session

base = [path 'sub-**_ses-' session '*'];

subj = dir(base); %check all matching subject for this session

addpath([path '/functions']) % load aknowledge functions
%check here https://github.com/munoztd0/fusy-octave-memories/blob/main/load_acq.m

for i=1:length(subj)

cd (physiodir) %go to the folder

subjO = char(subj(i).name);
subjX =  subjO(end-3:end); %remove .mat extension
filename = [subjX '.acq']; %add .acq extension
                

disp (['****** PARTICIPANT: ' subjX ' **** session ' session ' ****' ]);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% OPEN FILE
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


physio = load_acq(filename); %load and transform acknowledge file

data = physio.data; %or whatever the name is




%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CREATE AND SAVE THE CHANNEL
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%



cd (outdir) %go to the folder

% save the data as a file text in the participant directory
fid = fopen([subjX ',txt'],'wt');
for ii = 1:length(data)
    fprintf(fid,'%g\t',data(ii));
    fprintf(fid,'\n');
end
fclose(fid);

end 

希望能帮上忙！