EpiBioS4Rx EEG Upload

The study requires a minimum of 3 days (72 hours) or more of continuous EEG recording.

For more detailed de-identification and upload instructions please refer to our EpiBioS4Rx website http://epibios.loni.usc.edu/

The instructions can be found on My Dashboard > EpiBioS4Rx Documents & Links/ Human Subject Documents & Links > Current EpiBioS4Rx EEG Protocol

EEG De-identification and Conversion to EDF

  1. Obtain a 24 hr raw EEG file from your local EEG acquisition program (e.g. Moberg/Natus/Xltek). PLEASE KEEP A LOCAL COPY OF THE RAW EEG FILE.
  2. Copy the EEG file.
  3. Paste the EEG file onto your desktop.
  4. Open your Persyst software.
  5. Import copy of EEG file by clicking on the "Open" icon located on the top left-hand corner and choose the file. If the file does not appear, change the file type to that of the native acquisition tool, in example .e, .eeg, .cnt, .sdy. You can also drag and drop the file into Persyst.
  6. Once you are able to view your file via Persyst, go to the "Tools" icon located on left-hand side.
  7. Select "Clip/Export" (Persyst 12) or "Archive" (Persyst 13).
  8. A dialogue box will appear.
  9. Select the options to "De-identify patient" and "Export entire record."
  10. Select "Advanced<<."
  11. Ensure that "32-bit precision" is checked off in the Input/Output options.
    1. If the files has unused or physiological channel they will need to be removed by selecting "Select Channels" in the Input/Output Options section.
    2. A new dialogue box will appear with a list of all the channels. Click "Clear All," and select (blue) the channels for export. Make sure that you are exporting only head and depth channels, and not unused of physiological channels. Continue with the export below.
  12. Select "Clip/Export."
  13. Choose your desktop as the file destination.
  14. Save the file as an "EDF."
  15. The Persyst de-identification/conversion process will start (the process should take approximately 10-15 minutes in total).
  16. The file will be saved onto your desktop.
  17. Once Persyst is finished, locate the .edf EEG file and place in an empty folder on your desktop.
  18. Open the de-identified .edf EEG file in make sure that the patient information has been striped by selecting the "Patient" icon on the left hand side.
    1. Check that there are no issue with the file, if you notice anything unusual please contact the UCLA team as soon as possible.
    2. Check the file size of the file, if the file is under 2GB in size continue with Step 19, and the "Uploading to the IDA" instructions below. If the file is over 2GB in size, please contact the UCLA team to arrange an alternative upload option.
  19. Create another new empty folder on your desktop (this folder will serve as your "Target Directory" when uploading to the IDA).

Uploading to the IDA

If you have the IDA uploader on your computer:

*Use this method if your JAVA is not up to date*

  1. Open the IDA uploader program
  2. Enter your IDA credentials
  3. Select your site
  4. Select "Single Archive"
  5. Select the appropriate Research Group and Visit
  6. Enter your patient's Subject ID
  7. For the "Source Directory", select the folder that contains your de-identified EEG file
  8. For the "Target Directory", select the empty folder created in Step 17 of the "EEG De-identification and Conversion to EDF" section (please see above) The Target Directory is used by the IDA to place all of the data that it will not upload
  9. Select "Continue"
  10. The IDA will begin recognizing the files that are in the "Source Directory" folder and a list of recognized files will appear
  11. Ensure that the list contains only the files you would like to upload
  12. If all the files are correct, select "Submit". If not, select "Discard"and re-do Steps 4-11
  13. The upload process will begin (~5-10 min)
  14. ***PLEASE NOTE: The upload time will depend on the file size and the internet connection speed, so the time it takes to upload may be delayed. If time is an issue, you can have the IDA program running in the background.
  15. Wait until the progress bar is at 100%
  16. Select "Review Uploaded Files" to confirm that the EEG file was successfully uploaded to the IDA
  17. The desktop folder with the .edf EEG file can be saved to another location for your records
  18. You can leave the "Target Directory" folder onto your desktop for future IDA uploads

If you would like to upload via the IDA Website (REQUIRES JAVA):

  1. Go to the IDA website http://ida.loni.usc.edu/login.jsp?project=EPIBIOS4
  2. Enter your IDA credentials
  3. Select "Archive"
  4. Under Projects, choose EPIBIOS4@ "Your site"
  5. Select "Single Archive"
  6. Select the appropriate Research Group and Visit
  7. Enter your patient's Subject ID
  8. For the "Source Directory", select the folder that contains your de-identified EEG file
  9. For the "Target directory", select the empty folder created in Step 18 of the "EEG De-identification and Conversion to EDF" section (please see above). The Target Directory is used by the IDA to place all of the data that it will not upload
  10. Select "Continue"
  11. The IDA will begin recognizing the files that are in the "Source Directory" folder and a list of recognized files will appear
  12. Ensure that the list contains only the files you would like to upload
  13. If all the files are correct, select "Submit". If not, select "Discard"and re-do Steps 4-11
  14. The upload process will begin (~5-10 min)
  15. ***PLEASE NOTE: The upload time will depend on the file size and the internet connection speed, so the time it takes to upload may be delayed. If time is an issue, you can have the IDA program running in the background
  16. Wait until the progress bar is at 100%
  17. Select "Review Uploaded Files" to confirm that the EEG file was successfully uploaded to the IDA
  18. The desktop folder with the .edf EEG file can be saved to another location for your records
  19. You can leave the "Target Directory" folder onto your desktop for future IDA uploads

If you encounter any issues with the de-identification and upload process please contact the UCLA team as soon as possible.

Adapted from the EpibioS4Rx EEG Protocol V. 1.0