University of Leicester
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Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence

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posted on 2025-02-06, 12:10 authored by Joss Langford, Ahmed Barakat, Engy Daghash, Harvinder Singh, Alexander RowlandsAlexander Rowlands
Background: Following shoulder surgery, controlled and protected mobilisation for an appropriate duration is crucial for appropriate recovery. However, methods for objective assessment of sling wear and use in everyday living are currently lacking. In this pilot study, we aim to determine if a sling-embedded triaxial accelerometer and/or wrist-worn sensor can be used to quantify arm posture during sling wear and adherence to sling wear. Methods: Four participants were asked to wear a GENEActiv triaxial accelerometer on their non-dominant wrist for four hours in an office environment, and, for two of those hours, they also wore a sling in which an additional GENEActiv accelerometer was secured. During sling wear, they were asked to move their arm in the sling through a series of pre-specified arm postures. Results: We found that upper arm angle and posture type during sling wear can be predicted from a sling sensor alone (R2 = 0.79, p < 0.001 and Cohen’s kappa = 0.886, respectively). The addition of a wrist-worn sensor did not improve performance. The optimisation of an existing non-wear algorithm accurately detected adherence (99.3%). Conclusions: the remote monitoring of sling adherence and the quantification of immobilisation is practical and effective with digital health technology.

Funding

This research received funding from the Foxtrot Committee, Leicester Hospitals Charity (Ref: APP8407) for purchase of the accelerometers used in the study. A.V.R. was supported by the NIHR Leicester BRC and the NIHR Applied Research Collaboration (ARC), East Midlands (IS-BRC-1215-20010).

NIHR Leicester BRC

National Institute for Health Research

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History

Author affiliation

College of Life Sciences Population Health Sciences

Version

  • VoR (Version of Record)

Published in

Sensors

Volume

25

Issue

1

Pagination

166

Publisher

MDPI

eissn

1424-8220

Copyright date

2024

Available date

2025-02-06

Language

en

Deposited by

Dr Alex Rowlands

Deposit date

2025-01-18

Data Access Statement

The data that support the findings of this study are not openly available due to containing information that could compromise research participant privacy/consent. Requests for participant-level quantitative data and statistical codes should be made to the corresponding author.