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Toward Enhanced Clinical Decision Support for Patients Undergoing a Hip or Knee Replacement: Focus Group and Interview Study With Surgeons

Abstract:
The UK health service sees around 160,000 total hip or knee replacements every year and this number is expected to rise. Expectations of surgical outcome are changing alongside demographic trends, whilst aftercare may be fractured as a result of resource limitation or other factors. Conventional assessments of health outcomes must evolve to keep up with these changing trends. In practice, patients may visit a health care professional to discuss recovery and will provide survey feedback to clinicians using standardised instruments, such as the Oxford Hip & Knee score, in the months following surgery. To aid clinicians in providing accurate assessment of patient recovery a continuous home health care monitoring system would be beneficial. In this paper the authors explore how the SPHERE sensor network can be used to automatically generate measures of recovery from arthroplasty to facilitate continuous monitoring of behaviour, including location, room transitions, movement and activity; in terms of frequency and duration; in a domestic environment. The authors present a case study of data collected from a home equipped with the SPHERE sensor network. Machine learning algorithms are applied to a week of continuous observational data to generate insights into the domestic routine of the occupant. Testing of models shows that location and activity are classified with 86% and 63% precision, respectively
Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.2196/36172
Publication website:
http://eprints.worc.ac.uk/8902/1/Grant-CEUR.pdf

Authors

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Role:
Author
ORCID:
0000-0003-0148-9103
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Role:
Author
ORCID:
0000-0001-7405-4982
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Role:
Author
ORCID:
0000-0001-6552-8541
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Role:
Author
ORCID:
0000-0002-9940-1095
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Role:
Author
ORCID:
0000-0003-1067-5282


Publisher:
JMIR Publications
Journal:
JMIR Perioperative Medicine More from this journal
Volume:
6
Pages:
e36172-e36172
Publication date:
2023-04-24
DOI:
EISSN:
2561-9128
ISSN:
2561-9128


Language:
English
Keywords:
Pubs id:
1340151
Local pid:
pubs:1340151
Source identifiers:
W4366819732
Deposit date:
2026-05-07
ARK identifier:
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