BioSignals is a package for the Datagrok platform. The goal of the project is to offer an efficient and automated biosignal processing routine. The initial version is based on pyphysio - a python library developed by Andrea Bizzego.
The package reinforces the existing pyhton code with datagroks’ visualization and data processing tools. The pipeline itself is designed with scientific community in mind, standartizing and thus facilitating the usual ECG, EEG, EDA, etc. signal processing workflows. The fusion of manual and automated steps is largely enabled by our interactive viewers, scripting capabilities, detector functions,data augmentation,and a curated collection of scientific methods.
In particular, project’s initial goals are:
- automatically read various biosensor file formats
- integrate with the built-in file share browser
- provide efficient interactive visualizations for raw biosensor data
- including domain-specific visualizations, such as “head view” for EEG
- provide efficient ways for manipulating raw biosensor data (marking regions, etc)
- provide a collection of high-performance DSP algorithms
- detect type of signals, along with the metadata (sampling rate, etc)
- automatically suggest analyses and pipelines applicable to the current dataset
- Example: “Extract step count” for the accelerometry data
- visually define pipelines
- derive high-level features out of the raw biosensor signal
- allow to build predictive models by integrating previously defined pipelines with the Datagrok’s predictive modeling capabilities
- Example: training a model to find “bad” quality segments based on the manually annotated data
Currently, the project is in its early stages and we welcome you to contribute your ideas to this thread.