Noncontact Pulse Transit Time Measurement Using a Single-Frequency Continuous-Wave Radar

Tang, Mu-Cyun; Liao, Chien-Min; Wang, Fu-Kang; Horng, Tzyy‐Sheng

doi:10.1109/mwsym.2018.8439326

Cited by 23 publications

(13 citation statements)

References 13 publications

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“…In this study, we used an operating frequency of 79 GHz, whereas the other radar-based studies [30]- [34] used lower frequencies (Table VII). The advantage of use of a 79-GHz radar system is related to its high sensitivity to small displacements; the skin displacement caused by a pulse wave is typically less than 100 µm, which corresponds to radar echoes with phase rotations of less than 19.0 • , 5.8 • , and 0.58 • at frequencies of 79, 24, and 2.4 GHz, respectively.…”

Section: B Advantage and Disadvantage Of The Proposed Approachmentioning

confidence: 99%

“…Tao et al estimated the PWV using a radar system placed on the patient's upper arm and left ankle [29]. Tang et al [30] measured the PTT by measuring the displacement of the patient's arm and chest simultaneously using a radar system that the patient wore on their wrist. Lauteslager et al [31] measured the PTT by contacting six parts of the patient's body sequentially using a radar system.…”

Section: Introductionmentioning

confidence: 99%

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Experimental Demonstration of Accurate Noncontact Measurement of Arterial Pulse Wave Displacements Using 79-GHz Array Radar

2021

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In this study, we present a quantitative evaluation of the accuracy of simultaneous array-radar-based measurements of the displacements caused at two parts of the human body by arterial pulse wave propagation. To establish the feasibility of accurate radar-based noncontact measurement of this pulse wave propagation, we perform experiments with four participants using a 79-GHz millimeter-wave ultrawideband multiple-input multiple-output array radar system and a pair of laser displacement sensors. We evaluate the accuracy of the pulse wave propagation measurements by comparing the displacement waveforms that are measured using the radar system with the corresponding waveforms that are measured using the laser sensors. In addition, to evaluate the estimates of the pulse wave propagation channels, we compare the impulse response functions that are calculated from the displacement waveforms obtained from both the radar data and the laser data. The displacement waveforms and the impulse responses both demonstrated the good agreement between the results of the radar and laser measurements. The normalized correlation coefficient between the impulse responses obtained from the radar and laser data on average was as high as 0.97 for the four participants. The results presented here strongly support the feasibility of accurate radar-based noncontact measurement of arterial pulse wave propagation.

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Section: B Advantage and Disadvantage Of The Proposed Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental Demonstration of Accurate Noncontact Measurement of Arterial Pulse Wave Displacements Using 79-GHz Array Radar

2021

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“…By increasing F 1 (W ), the estimated echoŝ i (t) on the complex plane becomes flat and elongated, which is consistent with the small-displacement approximation in Eq. (10). However, this model alone cannot estimate multiple echoes from different parts of a human body.…”

Section: A Small-displacement Approximationmentioning

confidence: 99%

“…They attached them to the arm and leg and calculated the PTT and PWV from the delay time of the radar signals. Tang et al [10] used a wrist-worn device with a CW radar and a self-injection-locked radar. The user is supposed to keep the device in front of their chest to measure the pulse wave at the chest and wrist simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Signal Separation Using a Mathematical Model of Physiological Signals for the Measurement of Heart Pulse Wave Propagation With Array Radar

Sakamoto

2020

IEEE Access

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The arterial pulse wave, which propagates along the artery, is an important indicator of various cardiovascular diseases. By measuring the displacement at multiple parts of the human body, pulse wave velocity can be estimated from the pulse transit time. This paper proposes a technique for signal separation using an antenna array, so that pulse wave propagation can be measured in a non-contact manner. The body displacements due to the pulse wave at different body parts are highly correlated, and cannot be accurately separated using techniques that assume independent or uncorrelated signals. The proposed method formulates the signal separation as an optimization problem, based on a mathematical model of the arterial pulse wave. The objective function in the optimization comprises four terms that are derived based on a small-displacement approximation, unimodal impulse response approximation, and a causality condition. The optimization process was implemented using a genetic algorithm. The effectiveness of the proposed method is demonstrated through numerical simulations and experiments.

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“…Radar-based noncontact sensing is preferred to contact-type sensors (e.g., PPG) because it can provide unobtrusive monitoring of PWV data over long periods without causing discomfort to users. There are existing studies on radar-based pulse wave measurement [5][6][7][8][9][10]. In [5], a radar system was placed on the patient's upper arm and left ankle.…”

Section: Introductionmentioning

confidence: 99%

Generating a super-resolution radar angular spectrum using physiological component analysis

Sakamoto

2021

IEICE ComEX

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In this study, we propose a method for generating an angular spectrum using array radar and physiological component analysis. We develop physiological component analysis to separate radar echoes from multiple body positions, where echoes are phase-modulated by propagating pulse waves. Assuming that the pulse wave displacements at multiple body positions are constant multiples of a time-shifted waveform, the method estimates echoes using a simplified mathematical model. We exploit the mainlobe and nulls of the directional patterns of the physiological component analysis to form an angular spectrum. We applied the proposed method to simulated data to demonstrate that it can generate a super-resolution angular spectrum.

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Noncontact Pulse Transit Time Measurement Using a Single-Frequency Continuous-Wave Radar

Cited by 23 publications

References 13 publications

Experimental Demonstration of Accurate Noncontact Measurement of Arterial Pulse Wave Displacements Using 79-GHz Array Radar

Experimental Demonstration of Accurate Noncontact Measurement of Arterial Pulse Wave Displacements Using 79-GHz Array Radar

Signal Separation Using a Mathematical Model of Physiological Signals for the Measurement of Heart Pulse Wave Propagation With Array Radar

Generating a super-resolution radar angular spectrum using physiological component analysis

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