Respiration detection of sedentary person using ubiquitous WiFi signals

Ge, Y., Li, S., Zhu, S., Taha, A. , Cooper, J. , Imran, M. and Abbasi, Q. H. (2022) Respiration detection of sedentary person using ubiquitous WiFi signals. In: 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Denver, CO, USA, 10-15 Jul 2022, (Accepted for Publication)

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Abstract

No abstract available.

Item Type:Conference Proceedings
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ge, Mr Yao and Taha, Dr Ahmad and Abbasi, Dr Qammer and Imran, Professor Muhammad and Li, Shibo and Cooper, Professor Jonathan
Authors: Ge, Y., Li, S., Zhu, S., Taha, A., Cooper, J., Imran, M., and Abbasi, Q. H.
College/School:College of Science and Engineering
College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
College of Science and Engineering > School of Engineering > Biomedical Engineering
College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
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