OpenActigraphy was developed by the Stremler Research Lab , Lawrence S. Bloomberg Faculty of Nursing, University of Toronto. OpenActigraphy is the technology used in an award winning submission to the 2018 Healthy Behavior Data Challange.

We’re currently in closed beta testing but are looking for researchers with an interest in our solution to act as testers. Sign-up now to become a Beta Tester or sign up to be notified when we launch.

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Our Solution

The OpenActigraphy platform is cloud-based server where an automated analysis pipeline using research-validated algorithms is applied to generate objective measures of sleep, physical activity, and sedentary behavior. The analysis server works with multiple research-grade actigraphs. Our objective is to support any activity tracker device that is used in clinical research for sleep and/ or activity measurement.

Automated Analysis Pipeline

After data collection, our automated analysis pipeline uses your choice of research-validated analysis algorithms to generate results in seconds. If you already have previously collected sleep or activity data, those data can be uploaded and quickly processed.

Researcher Web UI

As a researcher you create an account on OpenActigraphy which lets you create project folders, manage participants (no-identifying data please), and process your data sets. When you’re finished, download all raw, processed, and summary data with quality graphs -in one step.

Data Access and Analytics

Are you interested in testing the system out but don’t have data? We have several demo data sets from prior studies available for platform trial purposes. Are you a data scientist looking to work with sleep and activity data? Our demo datasets could be a great place to get started.

Support for Custom Algorithms

Are you a data scientist with an amazing new sleep classifier to share with the world? You can implement it in OpenActigraphy and share it with the researchers.

Our Approach is “Open”

Our approach has been to build OpenActigraphy using open-source components and transparently implement research-quality algorithms validated in the scientific literature. Therefore, a scientist reviewing the data from OpenActigraphy can understand how the health indicators were calculated, the algorithms used and their implementation details. OpenActigraphy hopes to break research free of closed, proprietary accelerometer software, so that data may be analysed transparently.

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