Children with chronic musculoskeletal pain and healthy children were recruited from the Shriner's Hospital of Canada. All participants completed a resting-state EEG using the DSI-24, a 19-channel dry EEG headset. All children also completed quantitative sensory testing QST, with EEG recorded throughout the QST. This project compared the resting-state EEG to EEG recorded throughout a cold pressor task.
Milestone: manuscript submitted to Frontiers in Pain Research (currently in review)
All the code underlying the results presented in the manuscript referenced above are found in this repo.
The code for EEG feature generation is found in : Matlab Code. The code for the machine learning analysis, as well as the manuscript figures, is found in: Python code. The code for the basic descriptives of participant characteristics/demographics is found in: Other code.