MNE-Python version: 0.22.0 operating system: MacOS Mojave version 10.14 Hey guys, When I use find_bads_ecg() to find which ICs match the ECG pattern, it turns out that the ‘ecg_indices’ was empty no matter I modify the number of independent components as 15, 20, or 30. However, there did exist a …

Yeah there doesn’t seem to be much of an ECG artifact, so the peak finder will fail. Since there doesn’t seem to be a clear ECG signal in your data anyway, why do you still want to remove it? Seems like it doesn’t affect the recordings too much…

[image] YuZhou: but no matter how I tried the different options for qrs_threshold, the ecg plots just didn’t get much better. Since you don’t have a proper ECG channel in your data, find_ecg_events() synthesizes one. You can ask the function to return the synthesized signal by passing return_…

Hi Richard, I’m considering epoch my raw data first and then do the ica to see whether the ecg scalp map and the ecg evoked plot will get any better since there actually still many artifacts and noise in my raw data which although had been high-pass filtered and annotated muscle artifacts and remov…

I would really suggest to take a step back and figure out why the generation of ECG evokeds doesn’t seem to work properly. As long as we cannot figure that out, automated ECG rejection via ICA will most likely not work either

Okay, I follow your suggestions, ecg_events, ch_ecg, average_pulse, ecg = mne.preprocessing.find_ecg_events(raw_perception, return_ecg=True, verbose=True) ecg_epoch = mne.Epochs(raw_perception, ecg_events) ecg_evoked = ecg_epoch.average() ecg_evoked.apply_baseline(baseline=(None, -0.2)) ecg_evoked.…

[image] YuZhou: Number of ECG events detected : 680 (average pulse 100 / min.) That’s quite a high heart rate, did you expect this? Plot the detected events onto the raw data to see if they even make sense. raw_perception.plot(events=ecg_events)

[image] [image] [image] it seems unsual, the intervals between two adjacent ecg events have varying lengths, but how can this happen?

Obviously the automated ECG peak detection is not working, or the participant in question has some sort of cardiovascular condition…? What you can try is find a channel that appears to have a relatively clear ECG artifact and pass its ch_name to find_ecg_events(), and see if that produces any better…

Hi Richard, I checked another subject, same thing happened in him, so it’s not the problem of subjects. Then I tried to find the ecg artifacts in raw data plot according to the ecg pattern shown in the tutorial(the figure below): [image] But unfortunally, I didn’t found one in my data, here is w…

hhhh…… :joy: you’re absolutely right! Why should I, bother myself so much :joy: :joy: :joy: :joy: I just thought everybody has heartbeats, so the ecg must exist, which turns out it’s a wrong idea?

[image] YuZhou: I just thought everybody has heartbeats That’s what I’m hoping too! :sweat_smile: I’m not sure why there’s no strong ECG artifact in the magnetometer data. Maybe it has been pre-processed already? No idea…

Cannot find ecg artifacts during ica

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Cannot find ecg artifacts during ica

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