How to extract signal segments from a long signal given each segment's start and end points
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Hello,
I have a about 10-min signal sequence from the sensor, it looks like this:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/978620/image.png)
And I have labeled many sequence in this signal, the start-end point (time point) of each segment look like this:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/978625/image.png)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/978630/image.png)
Now I want to extract each segment as a vector without doing this by manually typing in their start-end point (ROI limits), so how can I do that?
I have an idea, which is using cell array to store those segments, but I don't know how to do that, may be using a loop, but how should I index them? Thanks!
Accepted Answer
Star Strider
on 26 Apr 2022
Perhaps —
First load ‘Time’ and ‘combinedAccel_01’ and ‘ROILimits’ into the workspace.
Then extract them to a cell array:
for k = 1:size(ROILimits,1)
idxrng = ROILimits(k,1) : ROILimits(k,2);
ROI{k} = [Time(idxrng) combinedAccel_01(idxrng)];
end
That should produce a cell array of column vectors of the time and data vectors.
Make appropriate changes depending on how the data are imported. Without hjaving them to work with, this is as far as I can go with the code.
.
2 Comments
Star Strider
on 26 Apr 2022
As always, my pleasure!
Rather than rounding, one option could be:
for k = 1:size(ROILimits,1)
idxrng = (Time >= ROILimits(k,1)) & (Time <= ROILimits(k,2));
ROI{k} = [Time(idxrng) combinedAccel_01(idxrng)];
end
The ‘idxrng’ variable is now a logical vector that can be used to reference the respective rows.
.
More Answers (1)
Image Analyst
on 26 Apr 2022
Can you extract value and then pass it to findgroups()? Then use that to extract the groups, like with indexing or the bwlabel() function. Attach your data if you need more help, but after reading this:
1 Comment
Image Analyst
on 26 Apr 2022
Maybe if you want to do stats on each group you can use splitapply(), grpstats(), or groupsummary().
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