Evaluation of at-home physiotherapy: machine-learning prediction with smart watch inertial sensors

Evaluation of at-home physiotherapy: machine-learning prediction with smart watch inertial sensors

Aims: An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodolog...

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Bibliographic Details
Main Authors: Philip Boyer, David Burns, Cari Whyne
Format: Article
Language:English
Published: The British Editorial Society of Bone & Joint Surgery 2023-03-01
Series:Bone & Joint Research
Subjects:
physiotherapy
physical therapy
rehabilitation
inertial measurement units
machine learning
shoulder
rotator cuff injuries
physiotherapists
rotator cuff
accelerometer
full-thickness rotator cuff tears
variances
standard deviation
flexion
Online Access:https://online.boneandjoint.org.uk/doi/epdf/10.1302/2046-3758.123.BJR-2022-0126.R1

Internet

https://online.boneandjoint.org.uk/doi/epdf/10.1302/2046-3758.123.BJR-2022-0126.R1

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