Skip to content
@OxWearables

Oxford Wearables Group

Code repository of the Wearables Group at the University of Oxford

Oxford Wearables Group

Software

PyPI About Repo Cite
accelerometer A Python Toolkit for Extracting Physical Activity and Behavior Metrics from Wearable Sensor Data OxWearables/biobankAccelerometerAnalysis Citation
actipy A Python toolkit to process wearable sensor data OxWearables/actipy Citation
stepcount Improved Step Counting via Foundation Models for Wrist-Worn Accelerometers OxWearables/stepcount Citation
asleep A sleep classifier for wearable sensor data using machine learning OxWearables/asleep Citation
actinet An activity classification model based on self-supervised learning for wrist-worn accelerometer data. OxWearables/actinet Citation

Latest Research

  • Fulda ES, Portas L, Harper C, Preiss D, Bennett D, Doherty A. Association of Daily Steps with Incident Non-Alcoholic Fatty Liver Disease: Evidence from the UK Biobank Cohort. Med Sci Sports Exerc. 2025 Apr 24:10.1249/MSS.0000000000003738. doi: 10.1249/MSS.0000000000003738. Epub ahead of print. PMID: 40279651; PMCID: PMC7617666. https://doi.org/10.1249/MSS.0000000000003738

  • Shreves AH, Small SR, Walmsley R, et alAmount and intensity of daily total physical activity, step count and risk of incident cancer in the UK BiobankBritish Journal of Sports Medicine Published Online First: 26 March 2025. doi: 10.1136/bjsports-2024-109360 https://doi.org/10.1136/bjsports-2024-109360

  • Chan, S., Hang, Y., Tong, C. et al. CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition. Sci Data 11, 1135 (2024). https://doi.org/10.1038/s41597-024-03960-3

  • Yuan, H., Hill, E. A., Kyle, S. D., & Doherty, A. (2024). A systematic review of the performance of actigraphy in measuring sleep stages. Journal of Sleep Research, 33(5), e14143. https://doi.org/10.1111/jsr.14143

  • Yuan, H., Plekhanova, T., Walmsley, R. et al. Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality. npj Digit. Med. 7, 86 (2024). https://doi.org/10.1038/s41746-024-01065-0

  • Small SR, Chan S, Walmsley R, VON Fritsch L, Acquah A, Mertes G, Feakins BG, Creagh A, Strange A, Matthews CE, Clifton DA, Price AJ, Khalid S, Bennett D, Doherty A. Self-Supervised Machine Learning to Characterize Step Counts from Wrist-Worn Accelerometers in the UK Biobank. Med Sci Sports Exerc. 2024 Oct 1;56(10):1945-1953. doi: 10.1249/MSS.0000000000003478. Epub 2024 May 15. PMID: 38768076; PMCID: PMC11402590. https://doi.org/10.1249/MSS.0000000000003478

  • Chen, Y., Chan, S., Bennett, D. et al. Device-measured movement behaviours in over 20,000 China Kadoorie Biobank participants. Int J Behav Nutr Phys Act 20, 138 (2023). https://doi.org/10.1186/s12966-023-01537-8

  • Yuan, H., Chan, S., Creagh, A.P. et al. Self-supervised learning for human activity recognition using 700,000 person-days of wearable data. npj Digit. Med. 7, 91 (2024). https://doi.org/10.1038/s41746-024-01062-3

  • Creagh, A.P., Hamy, V., Yuan, H. et al. Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis. npj Digit. Med. 7, 33 (2024). https://doi.org/10.1038/s41746-024-01013-y

Pinned Loading

  1. biobankAccelerometerAnalysis biobankAccelerometerAnalysis Public

    Extracting meaningful health information from large accelerometer datasets

    Python 222 68

  2. ssl-wearables ssl-wearables Public

    Self-supervised learning for wearables using the UK-Biobank (>700,000 person-days)

    Jupyter Notebook 134 35

  3. stepcount stepcount Public

    Improved Step Counting via Foundation Models for Wrist-Worn Accelerometers

    Jupyter Notebook 45 15

  4. actipy actipy Public

    Python Software Development Kit (SDK) to process wearable sensor data

    Python 24 11

Repositories

Showing 10 of 34 repositories
  • OxWearables/dnanexus-stepcount’s past year of commit activity
    Shell 1 1 0 0 Updated Oct 3, 2025
  • actinet Public

    An activity classification model based on self-supervised learning for wrist-worn accelerometer data.

    OxWearables/actinet’s past year of commit activity
    Python 9 2 0 0 Updated Oct 1, 2025
  • epidemiology_nhanes Public

    R code to perform basic all-cause mortality analyses with NHANES

    OxWearables/epidemiology_nhanes’s past year of commit activity
    2 2 0 0 Updated Sep 29, 2025
  • Oxford_Wearables_Activity_Recognition Public

    Notebooks for Oxford CDT Wearables Data Challenge

    OxWearables/Oxford_Wearables_Activity_Recognition’s past year of commit activity
    Jupyter Notebook 18 11 0 1 Updated Sep 24, 2025
  • WearableCollectionTutorial Public

    Practical on annotating wearable accelerometer and camera data

    OxWearables/WearableCollectionTutorial’s past year of commit activity
    Python 0 0 0 0 Updated Sep 19, 2025
  • stepcount Public

    Improved Step Counting via Foundation Models for Wrist-Worn Accelerometers

    OxWearables/stepcount’s past year of commit activity
    Jupyter Notebook 45 15 9 2 Updated Sep 19, 2025
  • actipy Public

    Python Software Development Kit (SDK) to process wearable sensor data

    OxWearables/actipy’s past year of commit activity
    Python 24 11 2 0 Updated Sep 13, 2025
  • asleep Public

    asleep: a sleep classifier for wearable sensor data using machine learning

    OxWearables/asleep’s past year of commit activity
    Python 35 11 15 (1 issue needs help) 0 Updated Aug 24, 2025
  • ukb_exome Public

    For conducting association analysis through UKB RAP

    OxWearables/ukb_exome’s past year of commit activity
    Python 0 0 0 0 Updated Aug 11, 2025
  • biobankAccelerometerAnalysis Public

    Extracting meaningful health information from large accelerometer datasets

    OxWearables/biobankAccelerometerAnalysis’s past year of commit activity
    Python 222 68 20 (2 issues need help) 4 Updated Jul 13, 2025