Fast and cost-effective method for non-contact respiration rate tracking using UWB impulse radar

Kakouche, Ibrahim; Maali, Abdelmadjid; Korso, Mohammed Nabil El; Mesloub, Ammar; Azzaz, Mohamed Salah

doi:10.1016/j.sna.2021.112814

Cited by 14 publications

(12 citation statements)

References 29 publications

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“…Specifically, we use the GGA to evaluate the Fourier transform (FT) at specific frequency indexes. Then, a complex band pass filter is applied to remove the clutter response and negative frequencies and enhance the VS waveform [4].…”

Section: Pre-processingmentioning

confidence: 99%

“…At this point, we apply the CBPF [28], presented in our previous work [4], to remove C m (ω) and enhance the VS waveform. The result of such a filter can be expressed as:…”

Section: Pre-processingmentioning

confidence: 99%

“…Non-contact vital sign (VS) detection, such as respiration rate, built upon a radio frequency (RF)-based system has attracted a great deal of interest in recent years. It is used in a growing field of applications, such as healthcare and clinical assistance, sleep and baby monitoring, survivor rescue and research operations, through the wall human detection, and human activity classification [1][2][3][4][5][6][7][8][9]. Recently, the impulse response ultra wide-band (IR-UWB) radar has gained more attention thanks to its high-range resolution, good penetration capability, and low power consumption [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…Notably, the phase variation on the received signal is exploited for this purpose [12]. To do so, several radar types have been investigated, including unmodulated continuous wave (CW) [13], frequencymodulated continuous-wave (FMCW) [14], step frequency continuous-wave (SFCW) [15], and IR-UWB [4]. Meanwhile, many signal processing techniques have been proposed, covering clutter rejection, human localization, and VS estimation [16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

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Joint Vital Signs and Position Estimation of Multiple Persons Using SIMO Radar

et al. 2021

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Respiration rate monitoring using ultra-wideband (UWB) radar is preferred because it provides contactless measurement without restricting the person’s privacy. This study considers a novel non-contact-based solution using a single-input multiple-output (SIMO) UWB impulse radar. In the proposed system, the collected radar data are converted to several narrow-band signals using the generalized Goertzel algorithm (GGA), which are used as the input of the designed phased arrays for position estimation. In this context, we introduce the incoherent signal subspace methods (ISSM) for the direction of arrivals (DOAs) and distance evaluation. Meanwhile, a beam focusing approach is used to determine each individual and estimate their breathing rate automatically based on a linearly constrained minimum variance (LCMV) beamformer. The experimental results prove that the proposed algorithm can achieve high estimation accuracy in a variety of test environments, with an error of 2%, 5%, and 2% for DOA, distance, and respiration rate, respectively.

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Section: Pre-processingmentioning

confidence: 99%

“…At this point, we apply the CBPF [28], presented in our previous work [4], to remove C m (ω) and enhance the VS waveform. The result of such a filter can be expressed as:…”

Section: Pre-processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Joint Vital Signs and Position Estimation of Multiple Persons Using SIMO Radar

et al. 2021

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“…Non-invasive monitoring of vital physiological activities such as breathing and heartbeat [ 9 , 10 ], and human physical activity [ 11 ] have been accomplished using UWB and continuous-wave (CW) radars. The ability to detect respiration-related motion in a human body has been reported in many works for UWB radar [ 12 , 13 , 14 ] and for CW radar [ 15 ]. Due to their low cost and high reliability, radar systems also have the potential to serve as an accurate monitor of breathing motion during radiotherapy.…”

Section: Introductionmentioning

confidence: 99%

Monitoring Respiratory Motion during VMAT Treatment Delivery Using Ultra-Wideband Radar

Fallatah

Bolić

MacPherson

et al. 2022

Sensors

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The goal of this paper is to evaluate the potential of a low-cost, ultra-wideband radar system for detecting and monitoring respiratory motion during radiation therapy treatment delivery. Radar signals from breathing motion patterns simulated using a respiratory motion phantom were captured during volumetric modulated arc therapy (VMAT) delivery. Gantry motion causes strong interference affecting the quality of the extracted respiration motion signal. We developed an artificial neural network (ANN) model for recovering the breathing motion patterns. Next, automated classification into four classes of breathing amplitudes is performed, including no breathing, breath hold, free breathing and deep inspiration. Breathing motion patterns extracted from the radar signal are in excellent agreement with the reference data recorded by the respiratory motion phantom. The classification accuracy of simulated deep inspiration breath hold breathing was 94% under the worst case interference from gantry motion and linac operation. Ultra-wideband radar systems can achieve accurate breathing rate estimation in real-time during dynamic radiation delivery. This technology serves as a viable alternative to motion detection and respiratory gating systems based on surface detection, and is well-suited to dynamic radiation treatment techniques. Novelties of this work include detection of the breathing signal using radar during strong interference from simultaneous gantry motion, and using ANN to perform adaptive signal processing to recover breathing signal from large interference signals in real time.

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