Novel Contactless Sensing Technique for Real-time Human Activity Detection

William Taylor; Ahmad Taha; Ahsen Tahir; Syed Aziz Shah; Qammer H. Abbasi; Muhammad Ali Imran

doi:10.1109/AP-S/USNC-URSI47032.2022.9886894

Novel Contactless Sensing Technique for Real-time Human Activity Detection

William Taylor
, Ahmad Taha
, Ahsen Tahir
, Syed Aziz Shah
, Qammer H. Abbasi
, Muhammad Ali Imran

University of Glasgow
University of Engineering and Technology Lahore

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

Abstract

Recent research has looked to implement real-time contactless sensing within a healthcare application which can pro-vide monitoring of vulnerable people living at home. Currently systems make use of wearable devices to achieve this but this requires users to always be wearing devices. This paper presents a real-time contactless system which makes use of radio frequency signal propagation to determine if a person is sitting or standing. This is achieved by observing incoming channel state information to detect movements and passing detected movements to an AI model that can predict sitting or standing motions from changes the signal amplitude described in the channel state information. The system is able to make accurate real-time classifications in multiple environments.

Original language	English
Title of host publication	2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1562-1563
Number of pages	2
ISBN (Electronic)	9781665496582
DOIs	https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9886894
State	Published - 2022
Externally published	Yes
Event	2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Denver, United States Duration: 10 Jul 2022 → 15 Jul 2022

Publication series

Name	2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings

Conference

Conference	2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022
Country/Territory	United States
City	Denver
Period	10/07/22 → 15/07/22

Keywords

Channel State Information
Human motion detection
Machine Learning
RF signals
Real-time

Access to Document

10.1109/AP-S/USNC-URSI47032.2022.9886894

Cite this

Taylor, W., Taha, A., Tahir, A., Shah, S. A., Abbasi, Q. H., & Imran, M. A. (2022). Novel Contactless Sensing Technique for Real-time Human Activity Detection. In 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings (pp. 1562-1563). (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9886894

Taylor, William ; Taha, Ahmad ; Tahir, Ahsen et al. / Novel Contactless Sensing Technique for Real-time Human Activity Detection. 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 1562-1563 (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings).

@inproceedings{bf88f4d5b3ba49a594806481f1dfcf84,

title = "Novel Contactless Sensing Technique for Real-time Human Activity Detection",

abstract = "Recent research has looked to implement real-time contactless sensing within a healthcare application which can pro-vide monitoring of vulnerable people living at home. Currently systems make use of wearable devices to achieve this but this requires users to always be wearing devices. This paper presents a real-time contactless system which makes use of radio frequency signal propagation to determine if a person is sitting or standing. This is achieved by observing incoming channel state information to detect movements and passing detected movements to an AI model that can predict sitting or standing motions from changes the signal amplitude described in the channel state information. The system is able to make accurate real-time classifications in multiple environments.",

keywords = "Channel State Information, Human motion detection, Machine Learning, RF signals, Real-time",

author = "William Taylor and Ahmad Taha and Ahsen Tahir and Shah, \{Syed Aziz\} and Abbasi, \{Qammer H.\} and Imran, \{Muhammad Ali\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 ; Conference date: 10-07-2022 Through 15-07-2022",

year = "2022",

doi = "10.1109/AP-S/USNC-URSI47032.2022.9886894",

language = "English",

series = "2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1562--1563",

booktitle = "2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings",

address = "United States",

}

Taylor, W, Taha, A, Tahir, A, Shah, SA, Abbasi, QH & Imran, MA 2022, Novel Contactless Sensing Technique for Real-time Human Activity Detection. in 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1562-1563, 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022, Denver, United States, 10/07/22. https://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9886894

Novel Contactless Sensing Technique for Real-time Human Activity Detection. / Taylor, William; Taha, Ahmad; Tahir, Ahsen et al.
2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. p. 1562-1563 (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings).

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

TY - GEN

T1 - Novel Contactless Sensing Technique for Real-time Human Activity Detection

AU - Taylor, William

AU - Taha, Ahmad

AU - Tahir, Ahsen

AU - Shah, Syed Aziz

AU - Abbasi, Qammer H.

AU - Imran, Muhammad Ali

PY - 2022

Y1 - 2022

N2 - Recent research has looked to implement real-time contactless sensing within a healthcare application which can pro-vide monitoring of vulnerable people living at home. Currently systems make use of wearable devices to achieve this but this requires users to always be wearing devices. This paper presents a real-time contactless system which makes use of radio frequency signal propagation to determine if a person is sitting or standing. This is achieved by observing incoming channel state information to detect movements and passing detected movements to an AI model that can predict sitting or standing motions from changes the signal amplitude described in the channel state information. The system is able to make accurate real-time classifications in multiple environments.

AB - Recent research has looked to implement real-time contactless sensing within a healthcare application which can pro-vide monitoring of vulnerable people living at home. Currently systems make use of wearable devices to achieve this but this requires users to always be wearing devices. This paper presents a real-time contactless system which makes use of radio frequency signal propagation to determine if a person is sitting or standing. This is achieved by observing incoming channel state information to detect movements and passing detected movements to an AI model that can predict sitting or standing motions from changes the signal amplitude described in the channel state information. The system is able to make accurate real-time classifications in multiple environments.

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KW - Human motion detection

KW - Machine Learning

KW - RF signals

KW - Real-time

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M3 - Conference contribution

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T3 - 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings

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BT - 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 10 July 2022 through 15 July 2022

ER -

Taylor W, Taha A, Tahir A, Shah SA, Abbasi QH, Imran MA. Novel Contactless Sensing Technique for Real-time Human Activity Detection. In 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. p. 1562-1563. (2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings). doi: 10.1109/AP-S/USNC-URSI47032.2022.9886894

Novel Contactless Sensing Technique for Real-time Human Activity Detection

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Keywords

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