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How can I get rid of baseline drift in an ecg without having the dfdt or advanced signal processing toolkits?

Hello,
I am recieving a lot of baseline drift in my ECG signal and was wondering how I can get rid of it? I saw examples at NI .com but they used the digital filter design toolkit and the advanced sgnal processing tollkit. I have neither one of these and since I am a student and this is my senior project I have no means to get these toolkits. I tried using a high pass filter but this did not work.\

Ray
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Ray,

When you say that something did not work, you are not giving much information for us to use to try to help you. Did the filter not work or did it not remove the drift?

How big is the drift, compared to the desired signal? How fast does it drift? How long are your sample sets? What are you doing with the ECG data? Looking at heart rate or analyzing a single-beat waveform for morphological changes? I think you can see that different end goals might require different approaches to baseline compensation.

If the drift is always fairly slow, you might be able to take small segments and subtract the mean of each segment. This may result in some offset or shift at the segment boundaries, but it is very simple and can easily be implemented without requiring a special toolkit.

Another approach is to low pass filter the ECG signal to extract an estimate of the baseline which can then be subtracted. Remember that all filters have a transient response and many will have a phase shift between the input and output.

Lynn
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I am working on ECG, Can you please explain what  a baseline drift and noise drift are in an ECG.
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You can implement a high-pass filter using basic LabVIEW arithmetic functions - see this Wikipedia article with included pseudocode implementation that can easily be created in LabVIEW:  http://en.wikipedia.org/wiki/High-pass_filter

 

 

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