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Welcome to the RNS_processing_toolbox wiki!
The purpose of the RNS processing toolbox is to provide general-use tools for downloading, manipulating, and viewing device data from NeuroPace.
The toolbox is split into python and matlab pipelines and toolsets. Python pipelines are used for downloading raw patient data, deidentifying it, and for interacting with Pennsieve. The Matlab toolbox contains useful data analysis and visualization tools that can be extended for your particular application.
Check out the Project Setup page to get started.
Data organization and python pipelines data flowchart:
- raw_processing: load in data from Box, de-identify .csv files, aggregate device data
- pensieve_pipeline (in progress): upload data to blackfynn, upload annotations
- pennsieve_tools: methods for interfacing with Pennsieve
- NPDataHandler: methods for raw NeuroPace data handling and conversion
- visualize: methods for visualizing the device data
- utils: utilities (date conversion, path handling, etc.)
- stim_detection_pipeline.m : detects start/stop indices and timepoints for stimulations occurring in device data
- findStim.m: detects stimulations
- idx2time.m: converts data index to datetime
- filterWindows: Finds windows that include and exclude a second set of windows