1. Handling Radar Cross-Section Performance in Monitoring Vital Signs Under Constraint Conditions
- Author
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Khan, Faheem, Sherazi, Saleh M., Khan, Naeem, Ashraf , Imran, Khan, Fahad, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Equipe Security, Intelligence and Integrity of Information (Lab-STICC_SI3), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), University of Science & Technology Bannu, HITEC University Taxila, Pakistan, This research has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 838037. The content of this paper only reflects the authors’ views and the Research Executive Agency is not responsible for any use that may be made of the information it contains., and European Project: 838037, UWB-IODA SF-PC
- Subjects
ARMA-model ,kalman filtering ,intermittent observations ,radar-cross section ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing ,vital signs - Abstract
The content of this paper reflects only the authors' view and the Research Executive Agency is not responsible for any use that may be made of the information it contains.; International audience; Two vital signs including heartbeat and respiratory rate are monitored in this work under two constraint situations; namely noise disturbance and intermittent observations. The existing scheme for finding, measuring and monitoring vital signs was Fourier Transform which could not deal with non-stationary process. As an alternative, the Wavelet Transform is used in this work which is equally applicable to both stationary and non-stationary processes. Additionally, the loss of output data may result in crucial implications in observing vital signs. Formerly, only un-interrupted data has been amalgamated in tracing vital signs. A novel adaptive ARMA-based scheme is proposed to obtain optimum estimated results in the presence of the above two critical scenarios. Simulation results obtained on real (practical) data show that the ARMA-based model produces similar vital signs as shown by clean and un-distorted data. It is shown that the proposed ARMA-based algorithm improves the breathing rate accuracy by 0.3% and heart rate accuracy by 2.5% as compared to the existing AR-based vital signal reconstruction algorithm.
- Published
- 2021
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