Utilizing 5G spectrum for healthcare to detect the tremors and breathing activity for multiple sclerosis

Haider, D., Ren, A. , Fan, D., Zhao, N., Yang, X., Tanoli, S. A. K., Zhang, Z., Hu, F., Shah, S. A. and Abbasi, Q. H. (2018) Utilizing 5G spectrum for healthcare to detect the tremors and breathing activity for multiple sclerosis. Transactions on Emerging Telecommunications Technologies, 29(10), e3454. (doi: 10.1002/ett.3454)

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Abstract

Utilizing fifth‐generation (5G) sensing in the health care sector with increased capacity and massive spectrum range increases the quality of health care monitoring systems. In this paper, 5G C‐band sensing operating at 4.8 GHz is used to monitor a particular body motion of multiple sclerosis patients, especially the tremors and breathing patterns. The breathing pattern obtained using 5G C‐band technology is compared with the invasive breathing sensor to monitor the subtle chest movements caused due to respiration. The 5G C‐band has a huge spectrum from 1 to 100 GHz, which enhances the capacity and performance of wireless communication by increasing the data rate from 20 Gb/s to 1 Tb/s. The system captures and monitors the wireless channel information of different body motions and efficiently identifies the tremors experienced since each body motion induces a unique imprint that is used for a particular purpose. Different machine learning algorithms such as support vector machine, k‐nearest neighbors, and random forest are used to classify the wireless channel information data obtained for various human activities. The values obtained using different machine learning algorithms for various performance metrics such as accuracy, precision, recall, specificity, Kappa, and F‐measure indicate that the proposed method can efficiently identify the particular conditions experienced by multiple sclerosis patients.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ren, Dr Aifeng and Abbasi, Dr Qammer and Shah, Mr Syed
Authors: Haider, D., Ren, A., Fan, D., Zhao, N., Yang, X., Tanoli, S. A. K., Zhang, Z., Hu, F., Shah, S. A., and Abbasi, Q. H.
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
College of Science and Engineering > School of Engineering
Journal Name:Transactions on Emerging Telecommunications Technologies
Publisher:Wiley
ISSN:2161-3915
ISSN (Online):2161-3915
Published Online:20 July 2018
Copyright Holders:Copyright © 2018 John Wiley and Sons Ltd
First Published:First published in Transactions on Emerging Telecommunications Technologies 29(10):e3454
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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