Processing data from a saved .mat file with a function

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Davide Cappelletto
Davide Cappelletto 2023 年 1 月 18 日
回答済み: Nikhilesh 2023 年 3 月 31 日
Hello,
I'm struggling with coming to a solution for this particular problem. I have created a function that takes data from a .c3d file and creates a structure and substructure with normalized data for every joint, every plane of motion, maximum, minimum, etc...
Now, I have to save the result of this function with a particular name, automatically if possible. Among the input variables, I always call a file which has the name of a test subject inside (ex: dinamica_giovanni.c3d ). I would like to implement an automatic save with that name inside the function.
After that, I have to place some of this data, depending on different movements (1 to 8) to one in 4 holes (whack a mole structure) and then process the results through anova tests etc...
I would like to create a function that loads a particular name-based, saved data from the previous point and process the data.
The input variables I would like to use are: structure of the test subject, hole number where the mole spawned, movements. For example:
output = function(subject_name, 1, 7)
also in this case, i would like to save my data in a structure (can be the output variable) that collect data every time i run the function
here is function n.1
acq = c3d2c3d(filename);
source = acq.c3dpar.point.labels;
elb_sagitt = acq.data{1,contains(source,'relbanglesxzy')}(:,1);
figure('Name','Intervals Selection')
plot(elb_sagitt);
title('Intervals Selection')
hold on
xr = round(ginput(intervals));
x = xr(:,1);
close 'Intervals Selection'
figure(2)
%Elbow Sagittal/Flexion-Extension
pos1 = [0.37 0.7 0.25 0.2];
subplot('Position',pos1);
plot(elb_sagitt)
ylim([0 120])
title('Elbow: flexion-extension')
elb_smat = [];
for ii = 1:2:intervals
elb_s = eventsnormalize(elb_sagitt,[x(ii) x(ii+1)],100);
elb_smat = cat(2,elb_s,elb_smat);
end
final.elbow.sagittal.data = elb_smat;
%Elbow Transversal/Internal-External Rotation
elb_transvers = acq.data{1,contains(source,'relbanglesxzy')}(:,3);
pos2 = [0.70 0.7 0.25 0.2];
subplot('Position',pos2);
plot(elb_transvers);
ylim([0 60])
title('Elbow: internal-external rotation')
elb_tmat = [];
for ii = 1:2:intervals
elb_t = eventsnormalize(elb_transvers,[x(ii) x(ii+1)],100);
elb_tmat = cat(2,elb_t,elb_tmat);
end
final.elbow.transversal.data = elb_tmat;
%Shoulder Sagittal/Flexion-Extension
sho_sagitt = acq.data{1,contains(source,'rshoanglesxzy')}(:,1);
pos3 = [0.04 0.4 0.25 0.2];
subplot('Position',pos3);
plot(sho_sagitt);
ylim([0 80])
title('Shoulder: flexion-extension')
sho_smat = [];
for ii = 1:2:intervals
sho_s = eventsnormalize(sho_sagitt,[x(ii) x(ii+1)],100);
sho_smat = cat(2,sho_s,sho_smat);
end
final.shoulder.sagittal.data = sho_smat;
%Shoulder Frontal/Ab-Adduction
sho_front = acq.data{1,contains(source,'rshoanglesxzy')}(:,2);
pos4 = [0.37 0.4 0.25 0.2];
subplot('Position',pos4);
plot(sho_front);
ylim([0 60])
title('Shoulder:ab-adduction')
sho_fmat = [];
for ii = 1:2:intervals
sho_f = eventsnormalize(sho_front,[x(ii) x(ii+1)],100);
sho_fmat = cat(2,sho_f,sho_fmat);
end
final.shoulder.frontal.data = sho_fmat;
%Shoulder Transversal/Internal-External Rotation
sho_transvers = acq.data{1,contains(source,'rshoanglesxzy')}(:,3);
pos5 = [0.70 0.4 0.25 0.2];
subplot('Position',pos5);
plot(sho_transvers);
ylim([0 60])
title('Shoulder: internal-external rotation')
sho_tmat = [];
for ii = 1:2:intervals
sho_t = eventsnormalize(sho_transvers,[x(ii) x(ii+1)],100);
sho_tmat = cat(2,sho_t,sho_tmat);
end
final.shoulder.transversal.data = sho_tmat;
%Wrist Sagittal/Flexion-Extension
wri_sagitt = acq.data{1,contains(source,'rwristanglesxzy')}(:,1);
pos6 = [0.19 0.1 0.25 0.2];
subplot('Position',pos6);
plot(wri_sagitt);
ylim([-30 30])
title('Wrist: flexion-extension')
wri_smat = [];
for ii = 1:2:intervals
wri_s = eventsnormalize(wri_sagitt,[x(ii) x(ii+1)],100);
wri_smat = cat(2,wri_s,wri_smat);
end
final.wrist.sagittal.data = wri_smat;
%Wrist Frontal/Ab-Adduction
wri_front = acq.data{1,contains(source,'rwristanglesxzy')}(:,2);
pos7 = [0.56 0.1 0.25 0.2];
subplot('Position',pos7);
plot(wri_front);
ylim([-30 30])
title('Wrist: ab-adduction')
wri_fmat = [];
for ii = 1:2:intervals
wri_f = eventsnormalize(wri_front,[x(ii) x(ii+1)],100);
wri_fmat = cat(2,wri_f,wri_fmat);
end
final.wrist.frontal.data = wri_fmat;
%RTrunk x
trunk_sagitt = acq.data{1,contains(source,'rtrunkangles')}(:,1);
pos8 = [0.04 0.7 0.25 0.2];
subplot('Position',pos8);
plot(trunk_sagitt)
title('Trunk')
tru_smat = [];
for ii = 1:2:intervals
tru_s = eventsnormalize(trunk_sagitt,[x(ii) x(ii+1)],100);
tru_smat = cat(2,tru_s,tru_smat);
end
final.trunk.sagittal.data = tru_smat;
final.elbow.sagittal.MAX.data = max(final.elbow.sagittal.data);
final.elbow.sagittal.MIN.data = min(final.elbow.sagittal.data);
final.elbow.sagittal.ROM.data = final.elbow.sagittal.MAX.data - final.elbow.sagittal.MIN.data;
final.elbow.sagittal.MAX.mean = mean(final.elbow.sagittal.MAX.data);
final.elbow.sagittal.MIN.mean = mean(final.elbow.sagittal.MIN.data);
final.elbow.sagittal.ROM.mean = mean(final.elbow.sagittal.ROM.data);
final.elbow.sagittal.MAX.std = std(final.elbow.sagittal.MAX.data);
final.elbow.sagittal.MIN.std = std(final.elbow.sagittal.MIN.data);
final.elbow.sagittal.ROM.std = std(final.elbow.sagittal.ROM.data);
final.elbow.transversal.MAX.data = max(final.elbow.transversal.data);
final.elbow.transversal.MIN.data = min(final.elbow.transversal.data);
final.elbow.transversal.ROM.data = final.elbow.transversal.MAX.data - final.elbow.transversal.MIN.data;
final.elbow.transversal.MAX.mean = mean(final.elbow.transversal.MAX.data);
final.elbow.transversal.MIN.mean = mean(final.elbow.transversal.MIN.data);
final.elbow.transversal.ROM.mean = mean(final.elbow.transversal.ROM.data);
final.elbow.transversal.MAX.std = std(final.elbow.transversal.MAX.data);
final.elbow.transversal.MIN.std = std(final.elbow.transversal.MIN.data);
final.elbow.transversal.ROM.std = std(final.elbow.transversal.ROM.data);
final.shoulder.sagittal.MAX.data = max(final.shoulder.sagittal.data);
final.shoulder.sagittal.MIN.data = min(final.shoulder.sagittal.data);
final.shoulder.sagittal.ROM.data = final.shoulder.sagittal.MAX.data - final.shoulder.sagittal.MIN.data;
final.shoulder.sagittal.MAX.mean = mean(final.shoulder.sagittal.MAX.data);
final.shoulder.sagittal.MIN.mean = mean(final.shoulder.sagittal.MIN.data);
final.shoulder.sagittal.ROM.mean = mean(final.shoulder.sagittal.ROM.data);
final.shoulder.sagittal.MAX.std = std(final.shoulder.sagittal.MAX.data);
final.shoulder.sagittal.MIN.std = std(final.shoulder.sagittal.MIN.data);
final.shoulder.sagittal.ROM.std = std(final.shoulder.sagittal.ROM.data);
final.shoulder.transversal.MAX.data = max(final.shoulder.transversal.data);
final.shoulder.transversal.MIN.data = min(final.shoulder.transversal.data);
final.shoulder.transversal.ROM.data = final.shoulder.transversal.MAX.data - final.shoulder.transversal.MIN.data;
final.shoulder.transversal.MAX.mean = mean(final.shoulder.transversal.MAX.data);
final.shoulder.transversal.MIN.mean = mean(final.shoulder.transversal.MIN.data);
final.shoulder.transversal.ROM.mean = mean(final.shoulder.transversal.ROM.data);
final.shoulder.transversal.MAX.std = std(final.shoulder.transversal.MAX.data);
final.shoulder.transversal.MIN.std = std(final.shoulder.transversal.MIN.data);
final.shoulder.transversal.ROM.std = std(final.shoulder.transversal.ROM.data);
final.shoulder.frontal.MAX.data = max(final.shoulder.frontal.data);
final.shoulder.frontal.MIN.data = min(final.shoulder.frontal.data);
final.shoulder.frontal.ROM.data = final.shoulder.frontal.MAX.data - final.shoulder.frontal.MIN.data;
final.shoulder.frontal.MAX.mean = mean(final.shoulder.frontal.MAX.data);
final.shoulder.frontal.MIN.mean = mean(final.shoulder.frontal.MIN.data);
final.shoulder.frontal.ROM.mean = mean(final.shoulder.frontal.ROM.data);
final.shoulder.frontal.MAX.std = std(final.shoulder.frontal.MAX.data);
final.shoulder.frontal.MIN.std = std(final.shoulder.frontal.MIN.data);
final.shoulder.frontal.ROM.std = std(final.shoulder.frontal.ROM.data);
final.wrist.sagittal.MAX.data = max(final.wrist.sagittal.data);
final.wrist.sagittal.MIN.data = min(final.wrist.sagittal.data);
final.wrist.sagittal.ROM.data = final.wrist.sagittal.MAX.data - final.wrist.sagittal.MIN.data;
final.wrist.sagittal.MAX.mean = mean(final.wrist.sagittal.MAX.data);
final.wrist.sagittal.MIN.mean = mean(final.wrist.sagittal.MIN.data);
final.wrist.sagittal.ROM.mean = mean(final.wrist.sagittal.ROM.data);
final.wrist.sagittal.MAX.std = std(final.wrist.sagittal.MAX.data);
final.wrist.sagittal.MIN.std = std(final.wrist.sagittal.MIN.data);
final.wrist.sagittal.ROM.std = std(final.wrist.sagittal.ROM.data);
final.wrist.frontal.MAX.data = max(final.wrist.frontal.data);
final.wrist.frontal.MIN.data = min(final.wrist.frontal.data);
final.wrist.frontal.ROM.data = final.wrist.frontal.MAX.data - final.wrist.frontal.MIN.data;
final.wrist.frontal.MAX.mean = mean(final.wrist.frontal.MAX.data);
final.wrist.frontal.MIN.mean = mean(final.wrist.frontal.MIN.data);
final.wrist.frontal.ROM.mean = mean(final.wrist.frontal.ROM.data);
final.wrist.frontal.MAX.std = std(final.wrist.frontal.MAX.data);
final.wrist.frontal.MIN.std = std(final.wrist.frontal.MIN.data);
final.wrist.frontal.ROM.std = std(final.wrist.frontal.ROM.data);
final.trunk.sagittal.MAX.data = max(final.trunk.sagittal.data);
final.trunk.sagittal.MIN.data = min(final.trunk.sagittal.data);
final.trunk.sagittal.ROM.data = final.trunk.sagittal.MAX.data - final.trunk.sagittal.MIN.data;
final.trunk.sagittal.MAX.mean = mean(final.trunk.sagittal.MAX.data);
final.trunk.sagittal.MIN.mean = mean(final.trunk.sagittal.MIN.data);
final.trunk.sagittal.ROM.mean = mean(final.trunk.sagittal.ROM.data);
final.trunk.sagittal.MAX.std = std(final.trunk.sagittal.MAX.data);
final.trunk.sagittal.MIN.std = std(final.trunk.sagittal.MIN.data);
final.trunk.sagittal.ROM.std = std(final.trunk.sagittal.ROM.data);

回答 (1 件)

Nikhilesh
Nikhilesh 2023 年 3 月 31 日
Hi Davide,
Please look at the documentation for " save " function.

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