I have kinematics data based on gait index which defines gait cycle based on 0-1000 gait index. One cycle consists about 546 data (not quite exact as due to sampling, data for new cycle might start after 0 and may also ends after 1000).
0 to 1000 may be normalized into 0% to 100%. If for example I have data that starts from 1.687262 and ends at 1000.866499 inclusive in that 546 data, how can I reduce the data into 101 data ranging exactly from 0% to 100% (0%, 1%, 2%, ... 100%)?
Thank you.
If your programming language is R, and you want to do interpolation, the link in below may be useful.
This provides spline interpolation.
https://www.rdocumentation.org/packages/stats/versions/3.6.0/topics/splinefun
And if you are using python, this link will also provide you the spline interpolation.
https://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html
I wish my suggestions will be helpful for you...
In MATLAB:
x = linspace(0, 100, length(your_data));
y = 0:100;
new_data = spline(x, your_data, y);
Just to update and share.
Obtained this simple and easy solution, copied directly from my m code using Matlab. GC is x-axis and hip and knee are y-axis. Copied from Excel into MATLAB workspace, test is an array with 1st column containing gait index (GI) and 2nd and 3rd columns both containing hip and knee angle in radian.
GC=test(:,1)/10; %normalize GI into % gait cycle
hip=test(:,2)*180/pi; %change radian into degree
knee=test(:,3)*180/pi; %change radian into degree
%interpolate hip & knee angles corresponding to 101 points gait cycle
GC_int=[0:1:100]'; %0% to 100%
hip_int=interp1(GC,hip,GC_int);
knee_int=interp1(GC,knee,GC_int); %spline interpolation
interpolate=[GC_int hip_int knee_int]; %copy variable & paste into excel
As GI starts at 1.687262 and ends at 1000.866499, y value at 0% is defined as NaN and there is interpolated value at 100% unless GI exactly starts from 0.
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