MATLAB: How to use the QRS Detection code from Simulink in MATLAB

cardiogramdigitalDSP System Toolboxecgecoprocessingsignal

I am following the Simulink example:

<https://www.mathworks.com/help/dsp/examples/real-time-ecg-qrs-detection.html https://www.mathworks.com/help/dsp/examples/real-time-ecg-qrs-detection.html >

I noticed that there is a MATLAB Fcn Block that has QRS Detection code. Is it possible to use this code in MATLAB, without having to create a Simulink model? If so, how do I achieve that?

Best Answer

This is certainly possible to do and all you need to do is copy-paste the code into a separate M file and use it like any other MATLAB function.

The more involved part will be processing the input argument "u" in a similar fashion to the one used in the example. The Simulink example's heart rate signal is filtered several times like so:

Raw heart rate signal

Buffer to 90 samples

Resample to 200Hz

Bandpass Filter

Differentiator Filter

Absolute Value

Discrete FIR Filter (moving average)

Then input to QRS Detection.

All the above Blocks have equivalent code or DSP System Toolbox functions that can be used in MATLAB scripts. For example. the Bandpass Filter Block has an equivalent function:

https://www.mathworks.com/help/dsp/ref/fdesign.bandpass.html

You can find alternatives in MATLAB code to all these Simulink Blocks and construct the example in MATLAB scripts.

Related Solutions

MATLAB: Remove the baseline wander

1)So I can't use a digital filter for processing the real time signal continuously?

I’m not aware of any MATLAB ability to do real-time digital filtering. The Audio Toolbox may have this ability, however I don’t have it so I have no experience with it.

2)I probably can save let's say 5 minutes of the signal and then filter it with a digital filter?

That’s certainly an option. The highpass and bandpass functions (R2018a and later) make the filter design much easier. (Return the second argument as the designeed filter, then use it with your signals with the filtfilt function to filter other signals.) If you don’t have those functions, it is easy to design an efficient ellliptic filter to do what you want.

For example:

Fs = 1000;                                          % Sampling Frequency
Fn = Fs/2;                                          % Nyquist Frequency
Wp = [859 862]/Fn;                                  % Passband Normalised
Ws = [855 865]/Fn;                                  % Stopband Normalised
Rp =  1;                                            % Passband Ripple (Irrelevant in Butterworth)
Rs = 50;                                            % Stopband Attenuation
[n,Wp] = ellipord(Wp,Ws,Rp,Rs);                     % Order Calculation
[z,p,k] = ellip(n,Rp,Rs,Wp);                        % Zero-Pole-Gain 
[sos,g] = zp2sos(z,p,k);                            % Second-Order Section For Stability
figure
freqz(sos, 2^16, Fs)                                % Filter Bode Plot
s_filt = filtfilt(sos, g, s);                       % Filter Signal

This designs a bandpass filter with passband frequencies of 859 to 862 Hz, and uses it fo filter signal vector ‘s’. For EKG signal processing, the passband would be 1 Hz to 100 Hz, with the stopbands of 0.5 Hz and 105 Hz.

MATLAB: Input signal –>abs block–>ideal low pass filter block–>output signal – Ideal low pass filter in Simulink

Simulink does not support an ideal filter block. As a substitute, a non-ideal filter with a very small transition band can be created. A filter structure of "Direct-form FIR" with a passband just below 3000Hz and a stopband of just over 3000Hz should achieve this. Below shows one example of this filter.

Frequency response for the above filter:

Alternatively, you can design your own filter using the Analog Filter Design block. This won't be an ideal filter either, but may be more desirable for your implementation. To examine the frequency response of, for instance, a custom Butterworth filter, see https://www.mathworks.com/help/signal/ref/butter.html. Other options include cheby1, cheby2, ellip, and besself.

Further information on the pre-R2015b Lowpass Filter Simulink block can be found here: https://www.mathworks.com/help/dsp/ref/lowpassfilterobsolete.html .

Best Answer

Related Solutions

MATLAB: Remove the baseline wander

MATLAB: Input signal –>abs block–>ideal low pass filter block–>output signal – Ideal low pass filter in Simulink

Related Question