Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals

Jakob Möderl; Erik Leitinger; Franz Pernkopf; Klaus Witrisal

Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals

Jakob Möderl^*, Erik Leitinger, Franz Pernkopf, Klaus Witrisal

^*Corresponding author for this work

Institute of Signal Processing and Speech Communication (4420)

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

Abstract

We present a variational message passing (VMP) approach to detect the presence of a person based on their respiratory chest motion using ultra-wideband (UWB) radar and to estimate the respiratory motion for contact-free vital sign monitoring. The received signal is modeled by a backscatter channel. The respiratory motion and propagation channel are estimated using VMP, while the presence of a person is detected by the evidence lower bound (ELBO). Numerical analyses and measurements demonstrate that the proposed method leads to a significant improvement in the detection performance compared to a fast fourier transform (FFT)-based detector or an estimator-correlator, since the multipath components (MPCs) are better incorporated into the detection procedure. Specifically, the proposed method has a detection probability of 0.95 at -20 dB signal-to-noise ratio (SNR), while the estimator-correlator and FFT-based detector have 0.32 and 0.05, respectively

Original language	English
Title of host publication	2023 IEEE International Conference on Acoustics, Speech, and Signal Processing
Number of pages	5
Publication status	Submitted - 13 Oct 2022
Event	48th IEEE International Conference on Acoustics, Speech, and Signal Processing: ICASSP 2023 - Rhodos, Greece Duration: 4 Jun 2023 → 9 Jun 2023

Conference

Conference	48th IEEE International Conference on Acoustics, Speech, and Signal Processing
Abbreviated title	ICASSP 2023
Country/Territory	Greece
City	Rhodos
Period	4/06/23 → 9/06/23

Access to Document

http://arxiv.org/abs/2210.07619Licence: CC BY-NC-SA 4.0

CD-Laboratory for Dependable Intelligent Systems in Harsh Environments
Pernkopf, F.
1/01/23 → 31/12/25
Project: Research project
SEAMAL Front - Securely Applied Machine Learning
Witrisal, K., Bischof, H., Schreiber, H. & Freiberger, G.
1/10/20 → 30/09/23
Project: Research project

Cite this

Möderl, J , Leitinger, E , Pernkopf, F & Witrisal, K 2022, Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals. in 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing. 48th IEEE International Conference on Acoustics, Speech, and Signal Processing, Rhodos, Greece, 4/06/23. <http://arxiv.org/abs/2210.07619>

@inproceedings{1de3cc8e0af94feba60d551153f9980a,

title = "Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals",

abstract = "We present a variational message passing (VMP) approach to detect the presence of a person based on their respiratory chest motion using ultra-wideband (UWB) radar and to estimate the respiratory motion for contact-free vital sign monitoring. The received signal is modeled by a backscatter channel. The respiratory motion and propagation channel are estimated using VMP, while the presence of a person is detected by the evidence lower bound (ELBO). Numerical analyses and measurements demonstrate that the proposed method leads to a significant improvement in the detection performance compared to a fast fourier transform (FFT)-based detector or an estimator-correlator, since the multipath components (MPCs) are better incorporated into the detection procedure. Specifically, the proposed method has a detection probability of 0.95 at -20 dB signal-to-noise ratio (SNR), while the estimator-correlator and FFT-based detector have 0.32 and 0.05, respectively",

author = "Jakob M{\"o}derl and Erik Leitinger and Franz Pernkopf and Klaus Witrisal",

year = "2022",

month = oct,

day = "13",

language = "English",

booktitle = "2023 IEEE International Conference on Acoustics, Speech, and Signal Processing",

note = "48th IEEE International Conference on Acoustics, Speech, and Signal Processing : ICASSP 2023, ICASSP 2023 ; Conference date: 04-06-2023 Through 09-06-2023",

}

TY - GEN

T1 - Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals

AU - Möderl, Jakob

AU - Leitinger, Erik

AU - Pernkopf, Franz

AU - Witrisal, Klaus

PY - 2022/10/13

Y1 - 2022/10/13

N2 - We present a variational message passing (VMP) approach to detect the presence of a person based on their respiratory chest motion using ultra-wideband (UWB) radar and to estimate the respiratory motion for contact-free vital sign monitoring. The received signal is modeled by a backscatter channel. The respiratory motion and propagation channel are estimated using VMP, while the presence of a person is detected by the evidence lower bound (ELBO). Numerical analyses and measurements demonstrate that the proposed method leads to a significant improvement in the detection performance compared to a fast fourier transform (FFT)-based detector or an estimator-correlator, since the multipath components (MPCs) are better incorporated into the detection procedure. Specifically, the proposed method has a detection probability of 0.95 at -20 dB signal-to-noise ratio (SNR), while the estimator-correlator and FFT-based detector have 0.32 and 0.05, respectively

AB - We present a variational message passing (VMP) approach to detect the presence of a person based on their respiratory chest motion using ultra-wideband (UWB) radar and to estimate the respiratory motion for contact-free vital sign monitoring. The received signal is modeled by a backscatter channel. The respiratory motion and propagation channel are estimated using VMP, while the presence of a person is detected by the evidence lower bound (ELBO). Numerical analyses and measurements demonstrate that the proposed method leads to a significant improvement in the detection performance compared to a fast fourier transform (FFT)-based detector or an estimator-correlator, since the multipath components (MPCs) are better incorporated into the detection procedure. Specifically, the proposed method has a detection probability of 0.95 at -20 dB signal-to-noise ratio (SNR), while the estimator-correlator and FFT-based detector have 0.32 and 0.05, respectively

M3 - Conference paper

BT - 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing

T2 - 48th IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 4 June 2023 through 9 June 2023

ER -

Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals

Abstract

Conference

Access to Document

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Projects

CD-Laboratory for Dependable Intelligent Systems in Harsh Environments

SEAMAL Front - Securely Applied Machine Learning

Cite this