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