An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings

Idongesit Ekerete; Chris Nugent; James McLaughlin

doi:10.1109/BIBM.2018.8621279

An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

237 Downloads (Pure)

Abstract

This paper proposes the use of unobtrusive sensing solutions to facilitate post-stroke rehabilitation exercises in home-based settings. Radar and thermal sensors are used to collect real-time data from a human subject as they perform rehabilitation exercises. The data collected is then compared with a gold standard exercise, which has been clinically prescribed, to allow feedback to be provided on how the exercises have been completed. The first iteration of the technical platform is presented and plans for its further development are outlined.

Original language	English
Title of host publication	2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Editors	Harald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
Pages	1478-1479
Number of pages	2
ISBN (Electronic)	978-1-5386-5488-0
DOIs	https://doi.org/10.1109/BIBM.2018.8621279
Publication status	Published (in print/issue) - 24 Jan 2019
Event	2018 IEEE International Conference on Bioinformatics and Biomedicine - Madrid, Spain Duration: 3 Dec 2018 → 6 Dec 2018 http://orienta.ugr.es/bibm2018/

Conference

Conference	2018 IEEE International Conference on Bioinformatics and Biomedicine
Abbreviated title	BIBM2018
Country/Territory	Spain
City	Madrid
Period	3/12/18 → 6/12/18
Internet address	http://orienta.ugr.es/bibm2018/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Post-stroke
Rehabilitation
Unobtrusive sensing

Access to Document

10.1109/BIBM.2018.8621279

2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)978-1-5386-5488-0/18/$31.00 ©2018 IEEEFinal published version, 123 KB

https://ieeexplore.ieee.org/document/8621279

Cite this

Ekerete, I., Nugent, C., & McLaughlin, J. (2019). An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, & L. Zhang (Eds.), 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1478-1479). Article 8621279 https://doi.org/10.1109/BIBM.2018.8621279

Ekerete, Idongesit ; Nugent, Chris ; McLaughlin, James. / An unobtrusive sensing solution for home based post-stroke rehabilitation : Proceedings. 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). editor / Harald Schmidt ; David Griol ; Haiying Wang ; Jan Baumbach ; Huiru Zheng ; Zoraida Callejas ; Xiaohua Hu ; Julie Dickerson ; Le Zhang. 2019. pp. 1478-1479

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title = "An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings",

abstract = "This paper proposes the use of unobtrusive sensing solutions to facilitate post-stroke rehabilitation exercises in home-based settings. Radar and thermal sensors are used to collect real-time data from a human subject as they perform rehabilitation exercises. The data collected is then compared with a gold standard exercise, which has been clinically prescribed, to allow feedback to be provided on how the exercises have been completed. The first iteration of the technical platform is presented and plans for its further development are outlined. ",

keywords = "Post-stroke, Rehabilitation, Unobtrusive sensing",

author = "Idongesit Ekerete and Chris Nugent and James McLaughlin",

year = "2019",

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doi = "10.1109/BIBM.2018.8621279",

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isbn = "978-1-5386-5487-3",

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editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",

booktitle = "2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",

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Ekerete, I , Nugent, C & McLaughlin, J 2019, An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings. in H Schmidt, D Griol, H Wang, J Baumbach, H Zheng, Z Callejas, X Hu, J Dickerson & L Zhang (eds), 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)., 8621279, pp. 1478-1479, 2018 IEEE International Conference on
Bioinformatics and Biomedicine, Madrid, Spain, 3/12/18. https://doi.org/10.1109/BIBM.2018.8621279

An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings. / Ekerete, Idongesit ; Nugent, Chris ; McLaughlin, James.
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). ed. / Harald Schmidt; David Griol; Haiying Wang; Jan Baumbach; Huiru Zheng; Zoraida Callejas; Xiaohua Hu; Julie Dickerson; Le Zhang. 2019. p. 1478-1479 8621279.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - An unobtrusive sensing solution for home based post-stroke rehabilitation

T2 - 2018 IEEE International Conference on<br/>Bioinformatics and Biomedicine

AU - Ekerete, Idongesit

AU - Nugent, Chris

AU - McLaughlin, James

PY - 2019/1/24

Y1 - 2019/1/24

N2 - This paper proposes the use of unobtrusive sensing solutions to facilitate post-stroke rehabilitation exercises in home-based settings. Radar and thermal sensors are used to collect real-time data from a human subject as they perform rehabilitation exercises. The data collected is then compared with a gold standard exercise, which has been clinically prescribed, to allow feedback to be provided on how the exercises have been completed. The first iteration of the technical platform is presented and plans for its further development are outlined.

AB - This paper proposes the use of unobtrusive sensing solutions to facilitate post-stroke rehabilitation exercises in home-based settings. Radar and thermal sensors are used to collect real-time data from a human subject as they perform rehabilitation exercises. The data collected is then compared with a gold standard exercise, which has been clinically prescribed, to allow feedback to be provided on how the exercises have been completed. The first iteration of the technical platform is presented and plans for its further development are outlined.

KW - Post-stroke

KW - Rehabilitation

KW - Unobtrusive sensing

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DO - 10.1109/BIBM.2018.8621279

M3 - Conference contribution

SN - 978-1-5386-5487-3

SP - 1478

EP - 1479

BT - 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

A2 - Schmidt, Harald

A2 - Griol, David

A2 - Wang, Haiying

A2 - Baumbach, Jan

A2 - Zheng, Huiru

A2 - Callejas, Zoraida

A2 - Hu, Xiaohua

A2 - Dickerson, Julie

A2 - Zhang, Le

Y2 - 3 December 2018 through 6 December 2018

ER -

An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings

Abstract

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Unobtrusive sensing solutions for home-based monitoring

Cite this

An unobtrusive sensing solution for home based post-stroke rehabilitation: Proceedings

Abstract

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Student theses

Unobtrusive sensing solutions for home-based monitoring

Cite this