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Remote cloud-based automated stroke rehabilitation assessment using wearables

Lookup NU author(s): Shane Halloran, Dr Jian Shi, Dr Yu Guan, Xi Chen, Michael Dunne-Willows, Professor Janet Eyre

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Abstract

© 2018 IEEE. We outline a system enabling accurate remote assessment of stroke rehabilitation levels using wrist worn accelerometer time series data. The system is built based on features generated from clustering models across sliding windows in the data and makes use of computation in the cloud. Predictive models are built using advanced machine learning techniques.


Publication metadata

Author(s): Halloran S, Shi JQ, Guan Y, Chen X, Dunne-Willows M, Eyre J

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings - IEEE 14th International Conference on eScience, e-Science 2018

Year of Conference: 2018

Pages: 302-302

Online publication date: 27/12/2018

Acceptance date: 02/04/2018

ISSN: 9781538691571

Publisher: IEEE

URL: https://doi.org/10.1109/eScience.2018.00063

DOI: 10.1109/eScience.2018.00063

Library holdings: Search Newcastle University Library for this item

ISBN: 9781538691564


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