University of Oxford
University · 13 recorded authors · 5 linked papers · 3 linked models
Logo: Wikimedia Commons · Public domain. Trademark of its owner, shown for identification only.
Highlights
- papers
- 5
- models
- 3
- authors
- 13
- SOTA
- 4
- Activity recognition · CAPTURE-24Cohen's κ 0.860 · ActiNet · reported in ActiNet · Share
- Activity recognition · CAPTURE-24Macro F1 0.818 · ActiNet · reported in ActiNet · Share
- Activity recognition · RealWorldMacro F1 0.661 · ActiNet · Share
- Activity recognition · WISDMMacro F1 0.741 · ActiNet · Share
+2 more SOTA results on the linked model pages.
Latest paper · 2026
CSFM: Cardiac Signal Foundation ModelThese connections come from recorded author affiliations. Linked works are deduplicated across those authors; they are not an institutional output ranking or proof that each work was produced here. Affiliations may be historical.
Researchers
Aidan AcquahShing ChanDavid A. CliftonLei Clifton
Andrew P. CreaghAiden DohertyXiao GuYuan HangFenglin LiuZhangdaihong LiuAbram SchonfeldtWei TangCatherine TongRecorded affiliation text (7)
- Big Data Institute, University of Oxford, Oxford, UK; Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Big Data Institute; Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Engineering Science, University of Oxford, Oxford, UK
- Oxford Suzhou Centre for Advanced Research, University of Oxford, Suzhou, China
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Department of Computer Science, University of Oxford, Oxford, UK
Source: the linked author records in the research atlas.
Linked models
Linked papers
ActiNet: an open-source tool for activity intensity classification of wrist-worn accelerometry using self-supervised deep learningScientific Reports · 2026
CSFM: Cardiac Signal Foundation ModelNature Machine Intelligence · 2026
CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognitionScientific Data · 2024
CAPTURE-24: Free-Living Wrist Accelerometer DatasetScientific Data · 2024
Self-supervised learning for human activity recognition using 700,000 person-days of wearable datanpj Digital Medicine · 2024
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