TY - GEN
T1 - Software Defined Radio Based Testbed for Large Scale Body Movements
AU - Ashleibta, Aboajeila Milad
AU - Zahid, Adnan
AU - Shah, Syed Aziz
AU - Imran, Muhammad Ali
AU - Abbasi, Qammer H.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7/5
Y1 - 2020/7/5
N2 - Monitoring Activities of Daily Livings (ADLs) has opened doors for numerous applications including patient monitoring, search rescue, intrusion detection and so on. However, the parameterssuch as operating frequency, transmitting power, and antenna design are static where each application requires particular hardware applications. This paper lays the foundation for ADLs and presents the design of the testbed based on Universal Software Radio Peripheral (USRP) in conjunction with omni directional antenna, that can be used for detecting large scale body movements such as walking, sitting, standing, and critical events such as falls and small-scale movements. The core idea is to extract the channel state information (CSI) from the received signal since each body motion produces a unique CSI signature. In this context, we have performed various human activities such as walking, sitting on a chair etc. in indoor environment using two USRPs. The experimental results indicate that each body motion can be visually identified by examining the CSI data.
AB - Monitoring Activities of Daily Livings (ADLs) has opened doors for numerous applications including patient monitoring, search rescue, intrusion detection and so on. However, the parameterssuch as operating frequency, transmitting power, and antenna design are static where each application requires particular hardware applications. This paper lays the foundation for ADLs and presents the design of the testbed based on Universal Software Radio Peripheral (USRP) in conjunction with omni directional antenna, that can be used for detecting large scale body movements such as walking, sitting, standing, and critical events such as falls and small-scale movements. The core idea is to extract the channel state information (CSI) from the received signal since each body motion produces a unique CSI signature. In this context, we have performed various human activities such as walking, sitting on a chair etc. in indoor environment using two USRPs. The experimental results indicate that each body motion can be visually identified by examining the CSI data.
KW - SDR
KW - human recognition based WCSI
UR - https://www.scopus.com/pages/publications/85101625915
U2 - 10.1109/IEEECONF35879.2020.9330027
DO - 10.1109/IEEECONF35879.2020.9330027
M3 - Conference contribution
AN - SCOPUS:85101625915
T3 - 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Proceedings
SP - 2079
EP - 2080
BT - 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020
Y2 - 5 July 2020 through 10 July 2020
ER -