Enhancement of Remote Vital Sign Monitoring Detection Accuracy Using Multiple-Input Multiple-Output 77 GHz FMCW Radar

Vodai, Toan Khanh; Oleksak, Kellen; Kvelashvili, Tsotne; Foroughian, Farnaz; Bauder, Chandler J.; Theilmann, Paul; Fathy, Aly E.; Kıłıc, Özlem

doi:10.1109/jerm.2021.3082807

Cited by 59 publications

(37 citation statements)

References 36 publications

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“…The large aperture of the virtual receive array enables the receiver to separate closely spaced targets. On establishing the relation of the proposed work to the above cited literature, we should note that [11] did not have features (ii) and (iii), while [12], [16] did not have features (i) and (iii).…”

Section: Introductionmentioning

confidence: 67%

“…As compared to the phased array, our TDM-phased MIMO with receive beamforming can more accurately estimate the BR and the HR of multiple subjects. Furthermore, compared to the state-of-the-art MIMO-based approach [12], which relies on a large antenna array (i.e., with 192 TX-RX antenna pairs), our solution achieves similar performance with the approach to BR detection (0.1 RMSE vs 0.2 RMSE) and HR estimation (0.6 RMSE vs 0.53 RMSE) in single target scenario while using a smaller array of only 8 TX-RX pairs. We believe that by implementing our method on the large antenna array used in [12], the performance of vital signal monitoring could be further improved.…”

Section: Multi-target Vital Sign Estimationmentioning

confidence: 99%

“…However, [11] reported preliminary BR and HR estimation performance of a single subject only (i.e., around 93% HR estimation and 96% BR estimation accuracy). Using a MIMO radar approach, [12] transmits mmWave signals via multiple transmitting antennas (TX) in a time-division-multiplexing (TDM) fashion, and use multiple receiving antennas (RX). By leveraging the TDMinduced orthogonality of the transmitted signals, each receive antenna can extract the contribution of each transmit antenna.…”

Section: Introductionmentioning

confidence: 99%

“…The contributions of different TX-RX pairs offer independent views of the targets, which can be exploited to improve target estimation. For example, [12] uses a MIMO radar with 12 TXs and 16 RXs, where in each time slot, only one of the available TXs transmits. The measurements collected over 12 slots correspond to 192 TX-RX antenna pairs, and can be used for high-precision vital sign monitoring with low estimation error.…”

Section: Introductionmentioning

confidence: 99%

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Simultaneous Monitoring of Multiple People’s Vital Sign Leveraging a Single Phased-MIMO Radar

Shi

Zhang

et al. 2022

IEEE J. Electromagn. RF Microw. Med. Biol.

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Vital sign monitoring plays a critical role in tracking the physiological state of people and enabling various healthrelated applications (e.g., recommending a change of lifestyle, examining the risk of diseases). Traditional approaches rely on hospitalization or body-attached instruments, which are costly and intrusive. However, in recent years there is an emergence of contactless vital sign monitoring techniques that rely on radio frequency signals. Early studies with continuous wave radars/WiFi devices have shown good success in detecting the vital signs of a single individual, while simultaneous monitoring of the vital signs of multiple, closely spaced subjects remains a challenge. In this paper, using an off-the-shelf Texas Instrument automotive FMCW radar, we design and implement a time-division multiplexing (TDM) phased-MIMO radar sensing system that allows high-precision vital sign monitoring of multiple subjects. The proposed sensing system can steer the beam towards the desired directions with a micro-second delay.The steerable beam enables capturing the vital signs of multiple individuals at the same radial distance to the radar. The proposed system enables the formation of a virtual array with aperture longer than that of the physical array. A Capon beamformer is used at the receiver side to combine the data collected from different transmit and receive antenna pairs corresponding to the virtual array. As all those pairs provide independent information about the targets, their combination significantly boosts the receiver signal-to-noise ratio. Based on the designed TDM phased-MIMO radar, we develop a system to automatically localize multiple human subjects and estimate their vital signs. Extensive evaluations show that under two-subject scenarios, our system can achieve more than 98.06% accuracy for breathing rate (BR) and more than 82.89% accuracy for heartbeat rate (HR) estimation, at a subject-to-radar distance of 1.6 m when the targets are facing the radar. The minimal subjectto-subject angle separation is 30 • at a subject-to-radar distance of 1.6 m, corresponding to a close distance of 0.3 m between two subjects, which outperforms the state-of-the-art.

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Section: Introductionmentioning

confidence: 67%

Section: Multi-target Vital Sign Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simultaneous Monitoring of Multiple People’s Vital Sign Leveraging a Single Phased-MIMO Radar

Shi

Zhang

et al. 2022

IEEE J. Electromagn. RF Microw. Med. Biol.

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“…At this stage, authors could only detect the cardiac signal if the subject was in apnea. Since then, the research community has evolved and several solutions have been proposed to separate respiratory and cardiac signals, without requiring the subject to hold his breath [7]- [21].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Heartbeat Signal Extraction Methods Using a 5.8 GHz Doppler Radar System in a Real Application Scenario

et al. 2022

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Doppler-based radar systems have been seen as a promising tool to assess vital signs, since they are capable to monitor the respiratory and cardiac signal remotely, by measuring the chest-wall displacement. However, due to the spectral overlap of these signals, their proper separation is a challenging task. In this paper, we demonstrate the effectiveness of using Discrete Wavelet Transform in the cardiac signal extraction, by comparing this method with other approaches widely used in literature, namely a standalone Band-Pass Filtering, the Ensembled Empirical Mode Decomposition, the Continuous Wavelet Transform and the Wavelet Packet Decomposition. The comparison metrics were defined taking into consideration the heart rate computation accuracy, and also the peak detection consistency to further evaluate the Heart Rate Variability. The efficiency of those methods is also tested considering real application scenarios, characterized by non-controlled monitoring environment conditions and the ability to equally assess the vital signs of different subjects, regardless their physical stature.

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基于毫米波雷达的智能心率提取方法

Feng,

Miao

2023

J. Shanghai Jiaotong Univ. (Sci.)

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Enhancement of Remote Vital Sign Monitoring Detection Accuracy Using Multiple-Input Multiple-Output 77 GHz FMCW Radar

Cited by 59 publications

References 36 publications

Simultaneous Monitoring of Multiple People’s Vital Sign Leveraging a Single Phased-MIMO Radar

Simultaneous Monitoring of Multiple People’s Vital Sign Leveraging a Single Phased-MIMO Radar

Evaluation of Heartbeat Signal Extraction Methods Using a 5.8 GHz Doppler Radar System in a Real Application Scenario

基于毫米波雷达的智能心率提取方法

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