Introducing Actigraphic Data Analyzer (ADA), an open source software for sleep/wake scoring and circadian rhythm analysis with graphical interface
New open-source software makes advanced actigraphic analysis accessible to researchers without programming expertise.
Researchers at the University of Warsaw and SWPS University have released Actigraphic Data Analyzer (ADA), a free and open-source Python package that brings comprehensive sleep/wake scoring and circadian rhythm analysis to a graphical interface. Published June 30, 2026 in Scientific Reports (PMID: 42380419), the tool addresses a long-standing gap between the sophistication of actigraphy research methods and the technical barriers that prevent many clinicians and sleep scientists from using them.
What it does
Actigraphy uses wrist-worn accelerometers to record movement over days or weeks, providing an objective window into sleep patterns and circadian rhythms outside the sleep laboratory. ADA reads raw accelerometer data from the two most widely used research-grade devices (GENEActiv and ActiGraph) as well as the public MESA (Multi-Ethnic Study of Atherosclerosis) dataset, then collapses the high-frequency signals into user-selectable epoch lengths.
For sleep/wake classification, the software implements multiple established algorithms alongside the recently published Universal Filter Approach, giving researchers flexibility to compare methods or choose the best fit for their data. For circadian rhythm analysis, ADA computes a comprehensive suite of descriptors including detrended fluctuation analysis (DFA), cosinor-based metrics (single, extended, and multiple components), autoregressive model spectra, interdaily stability (IS), intradaily variability (IV), and the timing and amplitude of M10 and L5 activity periods.
The package generates standard clinical sleep plots and metrics directly: daily activity profiles, sleep onset and offset markers, sleep fragmentation index, and related visualizations. Users can work through the interactive graphical interface or import ADA as a Python library for custom scripting.
Key technical details
ADA is written in Python and licensed under GPLv3, ensuring full transparency and reusability. The graphical interface lowers the technical barrier considerably: researchers who are comfortable with spreadsheet software can load raw accelerometer data, configure analysis parameters, and export results without writing a single line of code.
The developers validated the tool against real-world data by creating and releasing a new dataset of 87 weekly actigraphic recordings, made freely available under a Creative Commons CC-BY license. Analyzing these recordings allowed them to examine how different circadian rhythm descriptors relate to one another. A correlation matrix of the full descriptor set (DFA, cosinor variants, AR model spectrum, IS, IV, M10, L5) revealed that the metrics cluster into two meaningful groups: those primarily sensitive to circadian period length, and those that capture the strength or robustness of the 24-hour rhythm.
This finding underscores a practical insight for researchers: different circadian descriptors are not interchangeable, and studies that rely on a single metric may miss important facets of circadian physiology. ADA makes it straightforward to compute the full panel and examine these relationships.
Why it matters
Actigraphy sits at an awkward juncture in sleep research. The hardware is cheap and unobtrusive, the data is rich, and the clinical questions are urgent (how disrupted is this patient’s sleep? how fragmented is their circadian rhythm?). Yet the analytical pipeline has remained fragmented, with many research groups writing one-off scripts, relying on proprietary vendor software, or simply discarding the circadian rhythm dimension because the tools are too cumbersome.
By packaging the full analysis chain in a free, graphical, well-documented tool, ADA removes a real bottleneck. A clinician at a community sleep center, a graduate student new to actigraphy, or a collaborator in a field site with limited programming support can now run the same analyses as a specialized chronobiology lab. The open-source license also means the software can be audited, extended, and adapted by the community.
The release of the 87-recordings validation dataset under CC-BY is itself a contribution. Openly available actigraphy datasets with this depth of annotation are relatively scarce, and the accompanying analysis of descriptor clustering provides a useful reference for researchers designing circadian rhythm studies.
Limitations
ADA is a tool for analyzing actigraphy data, and actigraphy itself has well-known limitations. It infers sleep from movement (or its absence) rather than measuring brain states directly via polysomnography, so sleep/wake classification carries inherent uncertainty that varies by algorithm and population. The software’s accuracy depends on the quality of the input recordings and the appropriateness of the chosen algorithm for the specific study population.
The tool currently supports GENEActiv and ActiGraph devices plus the MESA dataset. Researchers using other accelerometer brands would need to convert their data into a compatible format. Additionally, while the graphical interface is a strength for accessibility, users who need to process very large datasets or run automated pipelines will want to use the Python library interface, which requires some programming familiarity.
Bottom line
ADA is a well-designed, freely available tool that fills a real gap in the actigraphy research ecosystem. Its combination of multiple sleep/wake scoring algorithms, comprehensive circadian rhythm descriptors, graphical interface, and open-source license makes it broadly useful across sleep research, clinical practice, and teaching. For any researcher working with GENEActiv or ActiGraph data who wants to go beyond basic sleep metrics into circadian rhythm analysis without building their own pipeline, ADA is worth a close look.
The software is available at the project repository (GPLv3), and the validation dataset of 87 weekly recordings is available under a CC-BY license.
Source: Bieganski P, Tutaj M, Duszyk-Bogorodzka A, Durka P. Introducing Actigraphic Data Analyzer (ADA), an open source software for sleep/wake scoring and circadian rhythm analysis with graphical interface. Sci Rep. 2026. doi:10.1038/s41598-026-59007-7. PMID: 42380419. Funding: Polish Minister of Education and Science (PN/01/0111/2022). No competing interests declared.