Open xhl1370 opened 2 years ago
It should not matter. The algorithm is designed to work for any sampling rate.
It should not matter. The algorithm is designed to work for any sampling rate.
But the graph doesn't detect the waveform
My data sample rate is 100Hz
Does it work if you try resampling it (with scipy.signal.resample for instance)? What's the duration of your signal (seconds, minutes)?
The signal lasts for eight or nine hours and is an electrocardiographic signal. The sampling rate is 100Hz, lower than 250Hz
Will the signal upsampling be distorted?
Will increasing the sample rate distort the signal? The code doesn't seem to work with signals below 250Hz
Assuming you are running main.py have you changed the value of the sampling rate in markers = ecg_delineator(ecg, sampling_rate = 500) by replacing 500 with 100? Otherwise, how are you running the algorithm? Are you feeding the whole 8 hours to the algorithm? Maybe try a shorter subset first? No, upsampling should not distort the signal. There is no reason for the method to fail for lower sampling rates specially given how clean your signal is.
![Uploading QQ图片20221017221544.png…]()
What I'm trying is 1000 samples, which is 10 seconds, and the sampling frequency is 100Hz
Maybe I could try upsampling, but generally I only use oversampling. Thank you very much for answering my question
Alright. Please try to resample the signal to 500 Hz for instance and see if the algorithm behaves differently.
thank you very much
This dataset uses apnea-ecg-database-1.0.0, I can detect the QRS waveform by upsampling
Is there an explanation for this code? I can't understand some places. If there is, I would really appreciate it
Which part can't you understand? Reading the original paper might help.
What if the sampling rate is less than 250?