A python package for the analysis of biopsychological data.
Project description
BioPsyKit
A Python package for the analysis of biopsychological data.
With this package you have everything you need for analyzing biopsychological data, including:
- Data processing pipelines for biosignals (ECG, EEG, ...)
- Methods for analyzing saliva samples (cortisol, amylase)
- Implementation of various psychological and HCI-related questionnaires
Additionally, there are modules to analyze and visualize data acquired from special measurement scenarios, such as:
- Montreal Imaging Stress Task (MIST)
- ... more to follow
Details
Biosignal Analysis
ECG Processing
BioPsyKit
provides a whole ECG data processing pipeline, consisting of:
- Loading ECG data from:
- generic
.csv
files - NilsPod binary (
.bin
) files (requiresNilsPodLib
: https://github.com/mad-lab-fau/NilsPodLib) - from other sensor types (coming soon)
- generic
- Splitting data into chunks (based on time intervals) that will be analyzed separately
- Perform ECG processing, including:
- R peak detection (using
Neurokit
: https://github.com/neuropsychology/NeuroKit) - R peak outlier removal and interpolation
- HRV feature computation
- ECG-derived respiration (EDR) estimation for respiration rate and respiratory sinus arrhythmia (RSA) (experimental)
- R peak detection (using
- Visualization of results
... more biosignals coming soon!
Biomarker Analysis
BioPsyKit
provides several methods for the analysis of biomarkers, such as:
- Load saliva data (e.g. cortisol and amylase) from deepwell plate Excel exports
- Compute standard features (maximum increase, slope, AUC, ...)
Questionnaires
BioPsyKit
implements various established psychological and HCI-related questionnaires, such as:
- Perceived Stress Scale (PSS)
- Positive Appraisal Negative Appraisal Scale (PANAS)
- Self-Compassion Scale (SCS)
- System Usability Scale (SUS)
- NASA Task Load Index (NASA-TLX)
- Short Stress State Questionnaire (SSSQ)
- ...
For more details, see the instructions in the questionnaire
module.
Stress Protocols
BioPsyKit
implements methods for analyzing data recorded with several established stress protocols, such as:
- Montreal Imaging Stress Task (MIST)
- Trier Social Stress Test (TSST) (coming soon...)
Installation
Install it via pip:
pip install biopsykit
For developer
git clone https://github.com/mad-lab-fau/BioPsyKit.git
cd biopsykit
poetry install
Install Python >3.8 and poetry. Then run the commands below to get the latest source and install the dependencies:
To run any of the tools required for the development workflow, use the doit commands:
$ poetry run doit list
docs Build the html docs using Sphinx.
format Reformat all files using black.
format_check Check, but not change, formatting using black.
lint Lint all files with Prospector.
test Run Pytest with coverage.
update_version Bump the version in pyproject.toml and biopsykit.__init__ .
Examples
See Examples in the function documentations on how to use this library.
Project details
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