Wi-Fi based passive human motion sensing for in-home healthcare applications

Bo Tan; Alison Burrows; Robert Piechocki; Ian  Craddock; Qingchao Chen; Karl Woodbridge; Kevin Chetty

doi:10.1109/WF-IoT.2015.7389123

Wi-Fi based passive human motion sensing for in-home healthcare applications

Bo Tan
, Alison Burrows
, Robert Piechocki
, Ian Craddock
, Qingchao Chen
, Karl Woodbridge
, Kevin Chetty

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

33 Citations (Scopus)

Abstract

This paper introduces a Wi-Fi signal based passive wireless sensing system that has the capability to detect diverse indoor human movements, from whole body motions to limb movements and breathing movements of the chest. The real time signal processing is used for human body motion sensing, and software defined radio demo system are described and verified in practical experiments scenarios, which include detection of through-wall human body movement, hand gesture or tremor, and even respiration. The experiment results offer potential for promising healthcare applications using Wi-Fi passive sensing in the home to monitor daily activities, to gather health data and detect emergency situations.

Original language	English
Title of host publication	2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)
Place of Publication	Milan, Italy
Publisher	IEEE
ISBN (Electronic)	978-1-5090-0366-2
ISBN (Print)	978-1-5090-0365-5
DOIs	https://doi.org/10.1109/WF-IoT.2015.7389123
Publication status	Published - 14 Dec 2015
Externally published	Yes
Publication type	A4 Article in conference proceedings

UN SDGs

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

SDG 3 Good Health and Well-being

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10.1109/WF-IoT.2015.7389123

Cite this

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title = "Wi-Fi based passive human motion sensing for in-home healthcare applications",

abstract = "This paper introduces a Wi-Fi signal based passive wireless sensing system that has the capability to detect diverse indoor human movements, from whole body motions to limb movements and breathing movements of the chest. The real time signal processing is used for human body motion sensing, and software defined radio demo system are described and verified in practical experiments scenarios, which include detection of through-wall human body movement, hand gesture or tremor, and even respiration. The experiment results offer potential for promising healthcare applications using Wi-Fi passive sensing in the home to monitor daily activities, to gather health data and detect emergency situations.",

author = "Bo Tan and Alison Burrows and Robert Piechocki and Ian Craddock and Qingchao Chen and Karl Woodbridge and Kevin Chetty",

year = "2015",

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doi = "10.1109/WF-IoT.2015.7389123",

language = "English",

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booktitle = "2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)",

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T1 - Wi-Fi based passive human motion sensing for in-home healthcare applications

AU - Tan, Bo

AU - Burrows, Alison

AU - Piechocki, Robert

AU - Craddock, Ian

AU - Chen, Qingchao

AU - Woodbridge, Karl

AU - Chetty, Kevin

PY - 2015/12/14

Y1 - 2015/12/14

N2 - This paper introduces a Wi-Fi signal based passive wireless sensing system that has the capability to detect diverse indoor human movements, from whole body motions to limb movements and breathing movements of the chest. The real time signal processing is used for human body motion sensing, and software defined radio demo system are described and verified in practical experiments scenarios, which include detection of through-wall human body movement, hand gesture or tremor, and even respiration. The experiment results offer potential for promising healthcare applications using Wi-Fi passive sensing in the home to monitor daily activities, to gather health data and detect emergency situations.

AB - This paper introduces a Wi-Fi signal based passive wireless sensing system that has the capability to detect diverse indoor human movements, from whole body motions to limb movements and breathing movements of the chest. The real time signal processing is used for human body motion sensing, and software defined radio demo system are described and verified in practical experiments scenarios, which include detection of through-wall human body movement, hand gesture or tremor, and even respiration. The experiment results offer potential for promising healthcare applications using Wi-Fi passive sensing in the home to monitor daily activities, to gather health data and detect emergency situations.

U2 - 10.1109/WF-IoT.2015.7389123

DO - 10.1109/WF-IoT.2015.7389123

M3 - Conference contribution

SN - 978-1-5090-0365-5

BT - 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)

PB - IEEE

CY - Milan, Italy

ER -

Wi-Fi based passive human motion sensing for in-home healthcare applications

Abstract

UN SDGs

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