peakdet 0.5.2

A Python toolbox for the identification and processing of peaks and troughs in physiological data

peakdet: A toolbox for physiological peak detection analyses

This package is designed for use in the reproducible processing and analysis of physiological data, like those collected from respiratory belts, pulse photoplethysmography, or electrocardiogram (ECG/EKG) monitors.

Overview

Physiological data are messy and prone to artifact (e.g., movement in respiration and pulse, ectopic beats in ECG). Despite leaps and bounds in recent algorithms for processing these data there still exists a need for manual inspection to ensure such artifacts have been appropriately removed. Because of this manual intervention step, understanding exactly what happened to go from "raw" data to "analysis-ready" data can often be difficult or impossible.

This toolbox, peakdet, aims to provide a set of tools that will work with a variety of input data to reproducibly generate manually-corrected, analysis- ready physiological data. If you'd like more information about the package, including how to install it and some example instructions on its use, check out our documentation <https://peakdet.readthedocs.io>_!

License Information

This codebase is licensed under the Apache License, Version 2.0. The full license can be found in the LICENSE <https://github.com/physiopy/peakdet/ blob/master/LICENSE>_ file in the peakdet distribution. You may also obtain a copy of the license at: http://www.apache.org/licenses/LICENSE-2.0.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Elizabeth DuPre 💻 🚇	Daniel Glen 🐛 💻 🚧	George Kikas 🐛 💻 🤔 🚇 👀 ⚠️	Ross Markello 🐛 💻 📖 🤔 🚇 🚧 🧑‍🏫 📆 👀 ⚠️ ✅
m-miedema 👀 🧑‍🏫	Stefano Moia 👀 🐛 💻 🤔 🚇 🧑‍🏫 📆	Marie-Eve Picard 📖 👀 🧑‍🏫	Taylor Salo 🚇
Rachael Stickland 📖 🚇 ⚠️	Mi-Xue Tan 💻 📓 🔌	Eneko Uruñuela 🚇	xl624 💻

This project follows the all-contributors specification. Contributions of any kind welcome!