Ashleibta, A. M., Taha, A. , Khan, M. A., Taylor, W. , Tahir, A., Zoha, A. , Abbasi, Q. H. and Imran, M. A. (2021) 5G-enabled contactless multi-user presence and activity detection for independent assisted living. Scientific Reports, 11, 17590. (doi: 10.1038/s41598-021-96689-7) (PMID:34475439) (PMCID:PMC8413293)
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Abstract
Wireless sensing is the state-of-the-art technique for next generation health activity monitoring. Smart homes and healthcare centres have a demand for multi-subject health activity monitoring to cater for future requirements. 5G-sensing coupled with deep learning models has enabled smart health monitoring systems, which have the potential to classify multiple activities based on variations in channel state information (CSI) of wireless signals. Proposed is the first 5G-enabled system operating at 3.75 GHz for multi-subject, in-home health activity monitoring, to the best of the authors’ knowledge. Classified are activities of daily life performed by up to 4 subjects, in 16 categories. The proposed system combines subject count and activities performed in different classes together, resulting in simultaneous identification of occupancy count and activities performed. The CSI amplitudes obtained from 51 subcarriers of the wireless signal are processed and combined to capture variations due to simultaneous multi-subject movements. A deep learning convolutional neural network is engineered and trained on the CSI data to differentiate multi-subject activities. The proposed system provides a high average accuracy of 91.25% for single subject movements and an overall high multi-class accuracy of 83% for 4 subjects and 16 classification categories. The proposed system can potentially fulfill the needs of future in-home health activity monitoring and is a viable alternative for monitoring public health and well being.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Zoha, Dr Ahmed and Taha, Dr Ahmad and Khan, Dr Muhammad Aurang and Ashleibta, Aboajeila Milad Abdulhadi and Abbasi, Professor Qammer and Tahir, Dr Ahsen and Imran, Professor Muhammad and Taylor, William |
Creator Roles: | Ashleibta, A. M.Conceptualization, Methodology, Investigation, Data curation, Writing – original draft, Writing – review and editing Taha, A.Conceptualization, Methodology, Validation, Investigation, Data curation, Writing – original draft, Writing – review and editing, Visualization, Project administration Khan, M. A.Conceptualization, Methodology, Formal analysis, Software, Data curation, Writing – original draft, Writing – review and editing, Visualization Taylor, W.Methodology, Formal analysis, Investigation, Software, Data curation, Visualization Tahir, A.Validation, Formal analysis, Software, Writing – original draft, Writing – review and editing Zoha, A.Writing – review and editing Abbasi, Q. H.Conceptualization, Methodology, Validation, Resources, Writing – review and editing, Supervision, Project administration, Funding acquisition Imran, M. A.Validation, Resources, Supervision, Project administration, Funding acquisition |
Authors: | Ashleibta, A. M., Taha, A., Khan, M. A., Taylor, W., Tahir, A., Zoha, A., Abbasi, Q. H., and Imran, M. A. |
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 |
Journal Name: | Scientific Reports |
Publisher: | Nature Research |
ISSN: | 2045-2322 |
ISSN (Online): | 2045-2322 |
Copyright Holders: | Copyright © 2021 The Authors |
First Published: | First published in Scientific Reports 11: 17590 |
Publisher Policy: | Reproduced under a Creative Commons License |
Data DOI: | 10.5525/gla.researchdata.1151 |
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