Unsolved mystery using average reference
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
Research direction
Start by reproducing the reported dataset behavior with pop_clean_rawdata using the shown options, comparing average reference and the 0.75–1.25 Hz versus 0.25–0.75 Hz filters. Trace the ASR rejection and its interaction with the average reference and high-pass filter. Done means explaining the 331-sample result and resolving the excessive rejection without breaking the 16000-sample cases.
Written by the indexing model from the issue text.
Description
Import this dataset.
Do average reference. Apply clean_rawdata with the default but changing the filter to 0.75 to 1.25 Hz. The resulting dataset crash because ASR rejection is too aggressive (331 samples left).
However, if you do not apply average reference with the same settings, then the size is 16000 samples. Also, if you use the default 0.25 to 0.75 filter, the size is 16000 (even with average reference).
options = {'FlatlineCriterion',5,'ChannelCriterion',0.85, ...
'LineNoiseCriterion',4,'Highpass',[0.75 1.25] ,'BurstCriterion',20, ...
'WindowCriterion',0.25,'BurstRejection','on','Distance','Euclidian', ...
'WindowCriterionTolerances',[-Inf 7] ,'fusechanrej',1};
pop_clean_rawdata(EEG, options{:});
There must be some weird problems in ASR and interaction between the average reference and HP filter. Need further investigation by a motivated soul.
- Dominant language
- MATLAB
- Stars
- 55
- Forks
- 19
- PR merge metrics
- No merged PRs in 30d
Contributor guide
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First steps
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