MATLAB: Help with Cross-correlation and Auto-correlation

auto-correlationcross correlationMATLAB

I don’t have that much experience in MATLAB, I hope someone can point me in the right direction, I am looking at breathing and the rate and various ways to detect this. I am currently looking into Cross correlation and auto correlation can somebody please help me setup some basic code and give me a few pointers.

I have attached a file which has 6000 samples, 100 samples per second, over 60 seconds.

Any help would be greatly appreciated.

Kind Regards

David

Best Answer

Try this:

s = load('raw_data.mat')
y = s.raw_ad_data_sine;
plot(y, 'b-', 'LineWidth', 2);
grid on;
% Find peaks
[peakValues, indexesOfPeaks] = findpeaks(y, 'MinPeakDistance', 200, 'Threshold', 1000);
% Plot them.

hold on;
plot(indexesOfPeaks, y(indexesOfPeaks), 'rv', 'LineWidth', 2, 'MarkerSize', 10);
% Find valleys
[valleyValues, indexesOfValley] = findpeaks(-y, 'MinPeakDistance', 200, 'Threshold', 1000);
valleyValues = -valleyValues;
% Plot them.
hold on;
plot(indexesOfValley, y(indexesOfValley), 'r^', 'LineWidth', 2, 'MarkerSize', 10);

Related Solutions

MATLAB: How to number the peaks and troughs of signal

Try findpeaks() in the Signal Processing Toolbox. Invert the signal to find valleys.

numPoints = 50;
x = sort(rand(1, numPoints));
y = rand(1, numPoints);
plot(x, y, 'k-', 'LineWidth', 2);
grid on;
[peakValues, indexesOfPeaks] = findpeaks(y);
hold on;
peakx = x(indexesOfPeaks);
peaky = y(indexesOfPeaks);
plot(peakx, peaky, 'r*', 'LineWidth', 2, 'MarkerSize', 10);
% Find valleys on inverted signal
[valleyValues, indexesOfValleys] = findpeaks(-y);
valleyx = x(indexesOfValleys);
valleyy = y(indexesOfValleys);
hold on;
plot(valleyx, valleyy, 'b*', 'LineWidth', 2, 'MarkerSize', 10);

Be careful with the first and last point of your data since it doesn't find those. You should look at the adjacent index (2 or end-1) if you want to classify them as either a peak or valley.

MATLAB: Peak Width at Half Height

See this demo:

% Initialization steps.
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 24;
% Make Gaussian https://en.wikipedia.org/wiki/Gaussian_function
x = linspace(0, 100, 1024);
amp = 50;
mu = 35;
sigma = 20;
y = amp * exp(-(x - mu).^2 / (2 * sigma^2));
hFig = figure;
plot(x, y, 'b-', 'LineWidth', 2);
grid on;
xlabel('x', 'FontSize', fontSize);
ylabel('y', 'FontSize', fontSize);
hFig.WindowState = 'maximized';
% Find the half height - midway between min and max y values.
halfHeight = (min(y) + max(y)) / 2;
hold on;
yline(halfHeight, 'Color', 'g', 'LineWidth', 2);
% Find left edge
index1 = find(y >= halfHeight, 1, 'first');
x1 = x(index1)
line([x1, x1], [0, y(index1)], 'Color', 'r', 'LineWidth', 2);
text(x1+1, 5, sprintf('x1 = %.2f', x1), 'FontSize', fontSize, 'Color', 'r');
% Find right edge
index2 = find(y >= halfHeight, 1, 'last');
x2 = x(index2)
line([x2, x2], [0, y(index2)], 'Color', 'r', 'LineWidth', 2);
text(x2+1, 5, sprintf('x2 = %.2f', x2), 'FontSize', fontSize, 'Color', 'r');
% Compute the full width, half max.
fwhm = x2 - x1
text(mu, halfHeight+2, sprintf('width = %.2f', fwhm), 'FontSize', fontSize, 'Color', 'r', 'HorizontalAlignment', 'center');
caption = sprintf('Full Width, Half Max = %.2f', x2 - x1);
title(caption,  'FontSize', fontSize);

Adapt code as needed for your variable names.

Best Answer

Related Solutions

MATLAB: How to number the peaks and troughs of signal

MATLAB: Peak Width at Half Height

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