Introducing Actigraphic Data Analyzer (ADA), an open source software for sleep/wake scoring and circadian rhythm...

Area of Science:

• Chronobiology
• Biomedical Data Analysis
• Software Development

Background:

• Actigraphy is crucial for objective sleep and circadian rhythm assessment.
• Existing software for actigraphy data analysis can be limited in scope or accessibility.
• Standardized analysis of circadian rhythm descriptors is needed.

Purpose of the Study:

• Introduce Actigraphic Data Analyser (ADA), a user-friendly, open-source Python package.
• Provide comprehensive tools for sleep and circadian rhythm analysis from raw actigraphy data.
• Facilitate the exploration of correlations between various circadian rhythm descriptors.

Main Methods:

• Developed ADA with a graphical user interface (GUI) and Python library functionality.
• Integrated data import from GENEActiv, ActiGraph devices, and the MESA dataset.
• Implemented multiple epoch collapsing methods, sleep/wake scoring algorithms (including Universal Filter Approach), and circadian rhythm analysis tools.
• Utilized a Python script to analyze correlations between circadian rhythm descriptors (DFA, cosinor, AR model spectrum, IS, IV, M10, L5) on a freely available dataset.

Main Results:

• ADA processes raw actigraphy data, offering versatile sleep/wake scoring and circadian rhythm analysis.
• The analysis of 87 weekly recordings revealed two distinct groups of circadian rhythm descriptors.
• One group correlates with circadian period length, while the other relates to the strength of the 24-hour rhythm.

Conclusions:

• Actigraphic Data Analyser (ADA) provides a powerful, accessible platform for sleep and circadian rhythm research.
• The study highlights a novel grouping of circadian rhythm descriptors based on their relationship to period length and rhythm strength.
• Both ADA and the associated dataset are freely available, promoting open science in chronobiology.