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Thank you,<br />
This question lies here for a really long time and I already managed to get the material I needed.<br />
Basically there are three issues in ECG signal analysis.<br />
<br />
1. Noise reduction using correlation with predicted noise and adaptive filtering.<br />
<br />
2. Detection of medical problems, this is surely done by analyzing wave shape for each heart beat and feeding the results to a decision logic systems or neural networks.<br />
<br />
3. Compression, this is done both in the time domain and by wavelet transform<br />
<br />
Using spectral analysis for heart rate measures is a huge overkill; all you have to do is simply detect the massive pick (QRS complex in the ECG language).<br />
<br />
<br />

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Thank you,
This question lies here for a really long time and I already managed to get the material I needed.
Basically there are three issues in ECG signal analysis.

1. Noise reduction using correlation with predicted noise and adaptive filtering.

2. Detection of medical problems, this is surely done by analyzing wave shape for each heart beat and feeding the results to a decision logic systems or neural networks.

3. Compression, this is done both in the time domain and by wavelet transform

Using spectral analysis for heart rate measures is a huge overkill; all you have to do is simply detect the massive pick (QRS complex in the ECG language).




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I need some direction to an article that describes EKG (or ECG) from the DSP prespective.
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I need some direction to an article that describes EKG (or ECG) from the DSP prespective.

DSP and EKG

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