Self-supervised machine learning to characterise step counts from wrist-worn accelerometers in the UK Biobank
<p><strong>Purpose:</strong> Step count is an intuitive measure of physical activity frequently quantified in health-related studies; however, accurate step counting is difficult in the free-living environment, with error routinely above 20% in wrist-worn devices against camera-ann...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Lippincott, Williams & Wilkins
2024
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