You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In cases where triggers are not used or are accidentally dropped, it could be useful to try predicting when scans are happening based on patterns in the signal. Some signals, like EDA and ECG, are dramatically affected by the pulse sequence, so we should be able to infer onsets and offsets with fairly high accuracy if those modalities are recorded.
Context / Motivation
The goal is to make it easier to convert data with missing trigger information.
Possible Implementation
I imagine that the implementation would be similar to the classification in #204, except applied to predicting time points/chunks in time series rather than classifying whole time series.
The text was updated successfully, but these errors were encountered:
Detailed Description
In cases where triggers are not used or are accidentally dropped, it could be useful to try predicting when scans are happening based on patterns in the signal. Some signals, like EDA and ECG, are dramatically affected by the pulse sequence, so we should be able to infer onsets and offsets with fairly high accuracy if those modalities are recorded.
Context / Motivation
The goal is to make it easier to convert data with missing trigger information.
Possible Implementation
I imagine that the implementation would be similar to the classification in #204, except applied to predicting time points/chunks in time series rather than classifying whole time series.
The text was updated successfully, but these errors were encountered: