create a script that will be able to analyze ecg, blood pressure and integrated msna signals and calculate the amplitude of msna, frequency and incidence of burst in matlab

To analyze ECG and blood pressure signals, we can use the built-in functions of MATLAB's Signal Processing Toolbox. To analyze the integrated MSNA signal, we need to first preprocess the signal by removing any DC offset, filtering out noise and extracting the bursts.

Assuming you have stored the signals in variables ecg, bp and msna, you can use the following code to calculate the MSNA amplitude, frequency and incidence of bursts:

main.m
% Remove DC offset from MSNA signal
msna = msna - mean(msna);

% Filter MSNA signal to remove noise
% Use a bandpass filter with passband between 0.1 Hz to 5 Hz to extract bursts
[b, a] = butter(2, [0.1 5]/(1000/2), 'bandpass');
msna_filt = filtfilt(b, a, msna);

% Calculate MSNA amplitude
amp = max(msna_filt) - min(msna_filt);

% Calculate MSNA frequency
[~, msna_peaks] = findpeaks(msna_filt);
if length(msna_peaks) > 1
    freq = 1000/mean(diff(msna_peaks));
else
    freq = 0;
end

% Calculate MSNA incidence of bursts
burst_threshold = 2*std(msna_filt); % set threshold as 2 standard deviations above mean
burst_idx = find(msna_filt > burst_threshold);
incidence = length(burst_idx)/length(msna_filt);

% Plot original and filtered MSNA signals
subplot(2,1,1);
plot(msna);
title('Original MSNA signal');
subplot(2,1,2);
plot(msna_filt);
title('Filtered MSNA signal');
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Note: This code assumes that the sampling frequency of your signals is 1000 Hz. If your signals have a different sampling frequency, you need to adjust the filter parameters accordingly.

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