MATLAB: Extract data between peaks

findpeaksMATLAB

Hello everyone, I would really appreciate help on solving this problem. I am trying to segment an emg data based on heelstrikes recorded from the accelerometer. I have used the peak to peak to find the location of the heelstrikes. The first peak, third and fifth peak belong to the right foot. The second, fourth,and sixth correspond to the left foot. I would like to extract the data between. Two heelstrikes of the same foot. For example I would like to write a for loop to extract the emg data from peak 1 to peak 3, then peak 3 to peak 5 till the last peak. Here's what I tried to do but it doesn't work. I have showed the extraction portion in the picture attached. Thanks in advance

if true
  % clear all
EMG = readmatrix('straightLASER01.xlsx','Sheet',1); %read emg data
ACC = readmatrix('straightLASER01.xlsx','Sheet',2); %read accleration data
[pks,locs] = findpeaks(ACC,'MinPeakDistance',1000); %find peaks 
 for p = 1:length(locs)
       first_strike = floor(locs(p,:));
       third_strike = floor(locs((p+2),:));
       acc = EMG1(first_strike:third_strike , p);
 end

end

Best Answer

This segregates the EMG1 data by every 2 right-foot steps.

rightFootIdx = 1 : 2 : numel(locs); 
for i = 1:length(rightFootIdx)-1
    acc = EMG1(locs(rightFootIdx(i)):locs(rightFootIdx(i+1)), p);
    % ...
end

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MATLAB: Extract and save data between two regions

Here's a rough idea that you can tweek so that it performs better. It involves calculating the slope of each line segment. The areas you circled have slopes much closer to 0 than the rest of the data so I followed these general rules to segregate those areas:

The slope of each segment must be "close to zero". This is defined as a slope between +/- 5 and is set by the "thr" threshold variable. However, there are lots of points that have a slope of 0 that aren't near those areas of interest and there are lots of points within those areas of interest that have a slope outside of these bounds. So more rules were needed.
If there is a series of data points that are all close to zero except for a few that are intermingled, they should be included. So if a slope is outside of the bounds (+/- thr) but within 40 indices to a point that is in the bounds, it's included. This window is set by the variable "wndw". This took care of the data points within the area of interest that had a bit larger slopes but there was still the problem of single data points here and there that had slopes near 0 but were far from the areas of interest. So we need the next rule.
There has to be at least 20 consecutive slopes near 0 or none of them are included. This is defined by the "minCount" variable. This took care of the occasional in-bound slopes that weren't in the area of interest.

I'll let you sift through this to figure out how it works. I recommend plotting some of the variables along the way. As you can see in the image (1/2 of your data), it's imperfect. But I haven't tweeked the 3 parameters mentioned above. You may need aditional rules (or an entirely different method).

% Read in the data
ACC = readmatrix('straightLASER011.xlsx','Sheet',1); %read emg data
x = (1:length(ACC))';  %Replace this with your x data; should be column vector!!!
% Find peaks
[pks,locs] = findpeaks(ACC,'MinPeakDistance',1000); %find peaks 
% Calculate slope at each segment
m = diff(ACC)-diff(x);
% Find slopes near 0
thr =5; %+/- thr from 0 is counted as "near 0"
isNearZero = abs(m)<thr; 
% Find groups of slopes near 0.  A group is defined as a slope that is 
% either near 0 or is within 'wndw' indices from a slope near 0.
wndw = 40; %window
% Calculate the start and stop of each grouping (this may need tweeking if you run into errors)
nearZeroIdx = find(isNearZero);             %index or nearZeros
nearZeroInt = diff(nearZeroIdx);            %interval between nearZeros
inWindowGrp = cumsum(nearZeroInt<=wndw);    %grouping by intervals within window
groupMarkers = [0;[0;diff([0;diff(inWindowGrp)]==1)]]; 
grpStart = nearZeroIdx(groupMarkers == 1); 
grpStop = nearZeroIdx([groupMarkers(2:end);-1] == -1); 
% Get rid of groups that aren't the min length
minCount = 20; % minimum number of near-0 to be considered a group.
groupTooSmall = (grpStop-grpStart) < minCount; 
grpStart(groupTooSmall) = []; 
grpStop(groupTooSmall) = []; 
% Extract sequences
seqIdx = arrayfun(@(srt,stp) srt:stp, grpStart,grpStop,'UniformOutput', false); 
% Plot it out
figure()
plot(x,ACC,'b-','LineWidth',2)   %Plot data
hold on
cellfun(@(i)plot(x(i),ACC(i),'r-','LineWidth',2),seqIdx) %plot areas of interest

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