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cardiopy-1.0.0


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توضیحات

Analysis package for single-lead clinical EKG data
ویژگی مقدار
سیستم عامل -
نام فایل cardiopy-1.0.0
نام cardiopy
نسخه کتابخانه 1.0.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Jackie Gottshall
ایمیل نویسنده jackie.gottshall@gmail.com
آدرس صفحه اصلی https://github.com/CardioPy/CardioPy
آدرس اینترنتی https://pypi.org/project/cardiopy/
مجوز -
# Cardiopy A flexibile package for R-peak detection and heart rate variability analysis of single-lead EKG data. <br> <img src="https://github.com/CardioPy/CardioPy/blob/master/example_run/advice_images/example_detections.png"> Full documentation is available [here](https://www.biorxiv.org/content/10.1101/2020.10.06.328856v1). If you use CardioPy or a derivative in your work, please cite: <br> Gottshall, J. L., Recoder, N., Schiff, N. D. (2020). CardioPy: An open-source heart rate variability analysis toolkit for single-lead EKG. boiRxv. doi: 10.1101/2020.10.06.328856 ## How to use Cardiopy Cardiopy can be used in two ways:<br> 1. __As a preprocessing module for the import and cleaning of clinical EKG data in conjuction with HRV analyses by standard software packages.__ For this use, run through feature sets 1 and 2 (listed below). The exported '*_nn.txt*' file is compatible with all major HRV software packages <br> 2. __As a stand-alone HRV analysis toolkit.__ For this use, continue through the workflow from feature set 1 through 4 (listed below). To ensure analytic reproducibilty, we highly recommend exporting cleaned nn detections at feature set 2. ## Features __1. Data preprocessing and cleaning__<br> * Load single-lead EKG data<br> * Detect R-peaks using the Pan Tompkins method - Option to detect R-peaks with flexible thresholding parameters for adjustment to noisy data and varying amplitudes<br> - Option to filter especially noisy data prior to peak detection<br> * Built-in detection visualization methods<br> * Simple artifact removal methods for manual inspection of detected peaks<br> __2. Export methods for cleaned peak detections__<br> * Compatible with commonly used software such as Kubios HRV and Artiifact<br> __3. HRV analysis methods__<br> * Standard time-domain statistics<br> * Standard frequency domain statistics<br> - Option for Multitaper or Welch power spectral estimates<br> __4. HRV statistics export__<br> * Single-file report exports in json format<br> * Multi-file exports into .csv spreadsheets for group statistics<br> ## Installation Use the package manager [pip](https://pip.pypa.io/en/stable/) to install CardioPy. ```bash pip install cardiopy ``` ## Usage Best when run with jupyter notebook. For detailed instructions download the [example jupyter notebook file](https://github.com/CardioPy/CardioPy/blob/master/example_run/CardioPy_Example_Analysis.ipynb) and the [example jupyter notebook file for manual cleaning](https://github.com/CardioPy/CardioPy/blob/master/example_run/CardioPy_Example_Analysis_Manual.ipynb), as well as the [de-identified data segment](https://github.com/CardioPy/CardioPy/blob/master/example_run/HCXXX_2001-01-01_awake_cycle1_epoch1_222000.csv) from [github](https://github.com/CardioPy/CardioPy/blob/master/example_run) <br> *For optimal performance, close figure interactions ('off' button on the top right corner) when finished with each window.* ### Parameter Optimization & Cleaning Tips * Remove false interbeat intervals LAST, after all cleaning (addition/removal of peaks) has been done. * To maintain integrity of the artifact logs: - Only remove incorrectly added peaks with EKG.undo_add_peak NOT with EKG.rm_peak. - Only re-add incorrectly removed peaks with EKG.undo_rm_peak NOT with EKG.add_peak. * If R peak detections are not accurate, try: 1. changing the moving window size 2. changing the upshift percentage 3. both<br> <img src="https://github.com/CardioPy/CardioPy/blob/master/example_run/advice_images/EKG_paramshift.png"> ## Contributing Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change. ## License BSD 3-Clause ## Roadmap The authors plan for future versions of CardioPy to include: * Support for additional commonly used data formats * A graphical user interface


نیازمندی

مقدار نام
- datetime
- matplotlib
- pandas
- scipy
- statistics
- mne
- numpy
- biosignalsnotebooks


زبان مورد نیاز

مقدار نام
>=3.6 Python


نحوه نصب


نصب پکیج whl cardiopy-1.0.0:

    pip install cardiopy-1.0.0.whl


نصب پکیج tar.gz cardiopy-1.0.0:

    pip install cardiopy-1.0.0.tar.gz