A Short-Time Autocorrelation Method for Noncontact Detection of Heart Rate Variability Using CW Doppler Radar

Nguyen, Nhan Thi Phuong; Lyu, Pei-Yu; Lin, Meng; Chang, Chia-Chan; Chang, Sheng-Fuh

doi:10.1109/imbioc.2019.8777797

Cited by 11 publications

(8 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In most of the existing studies including those in Refs. [7, 8, 10–17], the HR corresponds to the frequency with the maximum spectrogram power. However, when the noise is stronger than the heartbeat waveform, the frequency caused by noise may attain the maximum spectrogram power, leading to wrong HR estimation.…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…In most of the existing studies including the research studies in Refs. [7, 8, 10–17], the peak that has the maximum spectrogram power, which represents the frequency of 0.88 Hz in this example, should be selected as the HR. However, the reference result of the HR provided by ECG is 1.2 Hz rather than 0.88 Hz.…”

Section: Methodsmentioning

confidence: 99%

“…The fundamental principle of radar detecting HR is to measure the distance between the antenna and the body chest, which would be varying due to the pumping action of the heart. Research has been carried out using radars of different types such as the continuous‐wave (CW) radar [10–12], the frequency‐modulated CW (FMCW) radar [13–15] and the ultra‐wideband (UWB) radar [7, 16]. The feasibility of HR estimation with radar system is investigated in Refs.…”

Section: Introductionmentioning

confidence: 99%

“…In order to improve the quality of the heartbeat signal, short‐time autocorrelation is applied in Ref. [11] and a digital post‐distortion technique is proposed to compensate for the signal distortions in the digital baseband domain in Ref. [12].…”

Section: Introductionmentioning

confidence: 99%

“…The purpose of this study is to present a simple, robust, and accurate method for HR analysis under low SNR conditions. Different from the existing studies [7, 8, 10–17], the proposed method estimates the HR frequency of the radar data with low SNR from two levels, that is, coarse global estimation level and fine local estimation level. In the coarse estimation part, all the frequencies that are likely to be the HR are extracted at the global level of the entire spectrogram to generate the search region for the following estimation method, not just the frequency with the maximum magnitude.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Non‐contact monitoring of human heartbeat signals using mm‐wave frequency‐modulated continuous‐wave radar under low signal‐to‐noise ratio conditions

Zhang

Wang³

et al. 2021

IET Radar Sonar & Navi

View full text Add to dashboard Cite

Radar has been shown potentially to be used for non‐contact sensing of biosignals in a more comfortable and easier way than wearable and contact devices. By detecting and extracting body motions linked to physiological activities, accurate estimation of the heart rate is possible. However, the detection and estimation of heartbeat signal in practical applications is disturbed seriously by noise and respiration harmonic signal. In this study, a multi‐level coarse‐to‐fine method is proposed for heartbeat rate (HR) estimation with a frequency‐modulated continuous‐wave radar operating at 60 GHz utilised to extract the heartbeat information of human body under low signal‐to‐noise ratio conditions. First, the frequencies, which are likely to be the HR, are extracted in the coarse estimation part. Then, evaluations about the extracted frequencies are conducted in the fine estimation part. Finally, the multiple signal classification algorithm is utilised to separate the HR frequency from the respiration harmonics, which solves the frequency resolution issue caused by the observation window size, and achieves high accuracy estimation of HR. The experiments on measured data demonstrate the effectiveness of the proposed method. Compared with the state of the art, the proposed method has superiority in terms of estimation accuracy of HR.

show abstract

Section: The Proposed Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Non‐contact monitoring of human heartbeat signals using mm‐wave frequency‐modulated continuous‐wave radar under low signal‐to‐noise ratio conditions

Zhang

Wang³

et al. 2021

IET Radar Sonar & Navi

View full text Add to dashboard Cite

show abstract

Remote Vital Signs Measurement of Indoor Walking Persons Using mm-Wave FMCW Radar

Toda

2022

IEEE Access

View full text Add to dashboard Cite

Research on radar-based non-contact vital sign monitoring systems is critical during the COVID-19 epidemic. The accuracy of remote vital sign measurements has increased with the advancement of radar technology and various algorithms. Most studies require subjects to remain stationary, such as standing, sitting in a chair, or lying on a bed, and various measurement algorithms have been proposed. However, maintaining a stationary state as a prerequisite for measurement limits the development and application prospects of radar-based vital sign monitoring systems. Therefore, this paper presents a novel method for monitoring the vital signs of moving targets using a millimeter-wave frequency-modulated continuous-wave (FMCW) radar. The experimental results showed that regardless of whether the subjects walked at 1 m/s or with the left side of their body facing the radar, the accuracy of the heart rate measurement remained high. In the fixed-route experiments, the root mean squared error (RMSE) for heart rate estimation was 4.09 bpm, with an accuracy of 95.88%.INDEX TERMS FMCW radar, health care, heart rate, ICEEMDAN, radar signal processing, remote sensing, vital signs

show abstract

Non-Contact Heartbeat and Respiration Signal Detection Based on Improved Variational Mode Extraction

Zhou,

Lin,

et al. 2024

IEEE Access

View full text Add to dashboard Cite

A Short-Time Autocorrelation Method for Noncontact Detection of Heart Rate Variability Using CW Doppler Radar

Cited by 11 publications

References 10 publications

Non‐contact monitoring of human heartbeat signals using mm‐wave frequency‐modulated continuous‐wave radar under low signal‐to‐noise ratio conditions

Non‐contact monitoring of human heartbeat signals using mm‐wave frequency‐modulated continuous‐wave radar under low signal‐to‐noise ratio conditions

Remote Vital Signs Measurement of Indoor Walking Persons Using mm-Wave FMCW Radar

Non-Contact Heartbeat and Respiration Signal Detection Based on Improved Variational Mode Extraction

Contact Info

Product

Resources

About