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Accuracy of physical activity recognition from a wrist-worn sensor.

Cooper, Kay; Sani, Sadiq; Corrigan, Liam; MacDonald, Haley; Prentice, Chris; Vareta, Rob; Massie, Stewart; Wiratunga, Nirmalie


Sadiq Sani

Liam Corrigan

Haley MacDonald

Chris Prentice

Rob Vareta


The EU-funded project 'selfBACK' ( will utilise continuous objective monitoring of physical activity (PA) by a wrist-mounted wearable, combined with self-monitoring of symptoms and case-based reasoning. Together these will provide personalised self-management plans to people with low back pain via a novel digital health intervention. The purpose of this study was to determine the accuracy of PA recognition via wrist-mounted sensors compared to thigh-mounted sensors. Thigh or hip-mounted sensors have previously been shown to be the most accurate placement for single sensor-based PA monitoring. However, long-term adherence may be greatly enhanced with a less obtrusive wrist-worn sensor. It was therefore important to compare both locations.


COOPER, K., SANI, S., CORRIGAN, L., MACDONALD, H., PRENTICE, C., VARETA, R., MASSIE, S. and WIRATUNGA, N. 2017. Accuracy of physical activity recognition from a wrist-worn sensor. Presented at the 2017 Physiotherapy UK conference and trade exhibition: transform lives, maximise independence and empower populations, 10-11 November 2017, Birmingham, UK.

Presentation Conference Type Poster
Conference Name 2017 Physiotherapy UK conference and trade exhibition
Conference Location Birmingham, UK
Start Date Nov 10, 2017
End Date Nov 11, 2017
Deposit Date Feb 16, 2018
Publicly Available Date Feb 16, 2018
Keywords Physical activity; Digital health; Monitoring
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