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thanks for the great work. I found your repo while look for the SD1/SD2 implementation of poincare plot for my heart rate data in python.
It is great to see that you are making standard lib for the hrv calculation for python3. Can you give some hints about the min sample rate of heart rate for your api, since i am going to use it for the data optained by smartwatches, they have different sample rate als clinic ecg.
It will be really great if you can added the Lyapunov Exponent (LE) to the non-linear feature. It is always a great hiccup to get the LE correctly implemented.
Thanks again for keeping up this great work.
The text was updated successfully, but these errors were encountered:
thank you so much for the positive feedback! I am more than happy to see that this toolbox helps you support your work.
Regarding the Lyapunov exponent, I will definitely add this to the list of future features and have a closer look into it as soon as I have finished some other features I am working on focused on time-varying analysis.
Regarding the sampling rate, this toolbox is not limited to any specific sampling rate for the heart rate, given that the heart rate is not fixed by any sampling rate at all. However, if you are referring to the sampling rate of the ECG, I can recommend you to also have a look at the following papers:
Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis?:
In this work, the researchers investigated if a 50Hz sampling frequency for ECG signal acquisitions is enough for accurate extraction of heart rate series. Their research showed that reasonable time domain results could be achieved by applying a cubic spline interpolation on the acquired ECG data sampled at 50Hz from healthy subjects, however, the results might get distorted when applied on patients with existing heart conditions.
What is the adequate sampling interval of the ECG signal for heart rate variability analysis in the time domain?"
In this work, the researchers have searched for the most adequate sampling frequency, i.e. the
frequency at which interpolation is not required and where the use of higher sampling
frequencies would not provide any benefit. They recommend a sampling rate of 1kHz, which might be too high for your applications, but it might definitely be worth to have a look at.
I hope this information is helpful to you and let me know if I can be of any other help.
thanks for the great work. I found your repo while look for the SD1/SD2 implementation of poincare plot for my heart rate data in python.
It is great to see that you are making standard lib for the hrv calculation for python3. Can you give some hints about the min sample rate of heart rate for your api, since i am going to use it for the data optained by smartwatches, they have different sample rate als clinic ecg.
It will be really great if you can added the Lyapunov Exponent (LE) to the non-linear feature. It is always a great hiccup to get the LE correctly implemented.
Thanks again for keeping up this great work.
The text was updated successfully, but these errors were encountered: