pyActigraphy: Open-source python package for actigraphy data visualization and analysis

Area of Science:

• Chronobiology
• Sleep Science
• Biomedical Data Analysis

Background:

• Actigraphy has been a valuable tool for studying circadian rhythms and sleep patterns for 40 years.
• Growing interest exists in analyzing large population-based samples using actigraphy due to its ease of use.

Purpose of the Study:

• Introduce pyActigraphy, a comprehensive open-source Python package for actigraphy data analysis and visualization.
• Provide researchers with tools for in-depth and large-scale analysis of rest-activity patterns and sleep.
• Foster a community-driven software suite for actigraphy research.

Main Methods:

• The pyActigraphy package includes multiple sleep detection algorithms and rest-activity rhythm variables.
• It implements methods for reading diverse data formats and quantifying rhythm properties.
• Features include visualization of sleep agendas, automatic rest period detection, and advanced signal processing.

Main Results:

• pyActigraphy offers a unified platform for comprehensive actigraphy data analysis.
• The package supports various data formats and includes multiple algorithms for sleep and rhythm analysis.
• It facilitates advanced signal processing and visualization for research.

Conclusions:

• pyActigraphy provides a robust, open-source solution for analyzing actigraphy data.
• The package aims to standardize and advance the analysis of rest-activity patterns in large populations.
• It serves as a foundation for a collaborative, community-supported software suite in chronobiology and sleep research.