Overnight non-contact continuous vital signs monitoring using an intelligent automatic beam-steering Doppler sensor at 2.4 GHz

Batchu, Satish; Narasimhachar, H.; Mayeda, Jill C.; Hall, Travis; Lopez, Jerry; Nguyên, Tam; Banister, Ronald E.; Lie, Donald Y. C.

doi:10.1109/embc.2017.8036936

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Also in the context of long term monitoring applications, such as overnight sleeping monitoring, adaptive solutions using phased-array techniques have been explored in [45]. Based on the prototype presented in [44], a single PCB was developed with a view to decrease the front-end size, minimize cables loss and improve signals detection accuracy.…”

Section: Phased-array Antennas Beamforming Techniques and Other Amentioning

confidence: 99%

A Review on Methods for Random Motion Detection and Compensation in Bio-Radar Systems

Gouveia

Vieira

Pinho

2019

Sensors

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The bio-radar system can measure vital signals accurately, by using the Doppler effect principle, which relates the received signal properties to the distance change between the radar antennas and the subject chest-wall. These systems have countless applications, from short range detection to assist in rescue missions, to long-term applications as for the continuous sleeping monitoring. Once the main applications of these systems intend to monitor subjects during long periods of time and under noisy environments, it is impossible to guarantee the patient immobilization, hence its random motion, as well as other clutter sources, will interfere in the acquired signals. Therefore, the signal processing algorithms developed for these applications have been facing several challenges regarding the random motion detection and mitigation. In this paper, an extended review on the already implemented methods is done, considering continuous wave radars. Several sources of random motion are considered, along with different approaches to compensate the distortions caused by them.

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Section: Phased-array Antennas Beamforming Techniques and Other Amentioning

confidence: 99%

A Review on Methods for Random Motion Detection and Compensation in Bio-Radar Systems

Gouveia

Vieira

Pinho

2019

Sensors

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“…Efforts to achieve non-contact RRI estimation have led to the exploration of Doppler sensors (Pan et al, 2022). These sensors, designed to observe the velocity and direction of a moving target, operate by transmitting microwaves towards the target and analyzing the reflected Doppler-shifted microwaves (Batchu et al, 2017;W. Hu et al, 2014;Munoz-Ferreras et al, 2018;Ren et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Innovative non-contact r-r intervals estimation using viterbi algorithm with Squared Branch Metric (VSBM)

Zar,

Tun,

Win

et al. 2024

JPTK

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Non-contact heartbeat detection by using Doppler sensor is a critical component of remote health monitoring systems, enabling continuous and unobtrusive monitoring of an individual’s cardiovascular health. In this paper, we reported an innovative approach for non-contact heartbeat detection using the Viterbi algorithm, leveraging the distribution of the difference of two adjacent R-R intervals (RRIs). RRIs represent the time between successive peaks in the electrocardiogram (ECG) signal and are fundamental in analyzing heart rate variability, mental stress conditions and heart diseases. Numerous non-contact Doppler sensor-based methods have been proposed for heartbeat detection, leveraging the evaluation of RRIs without physical device attachment. However, challenges arise from unwanted peaks introduced by respiration and slight body movements, even when the subject remains motionless with normal breathing. This study presented an innovative approach for selecting heartbeat peaks utilizing the Viterbi algorithm with the squared difference of two adjacent RRIs as the Branch metric (BM). Our preliminary experiments reveal that the difference between two adjacent RRIs closely follows a Gaussian distribution. Building upon this observation, we considered the Viterbi algorithm with Squared Branch Metric (VSBM) to estimate the heartbeat accurately. To assess the accuracy of our peak selection method, we conducted experiments comparing it with two existing peak detection methods: (i) Doppler output after Low-Pass Filter (LPF)-based method and (ii) Spectrogram-based method. Our results demonstrate that the proposed VSBM method is effective to detect the heartbeat accurately for each peak detection method. Furthermore, we compared the performance of “Spectrogram + VSBM” outperforms the “Doppler output after LPF + VSBM” method by the Root-Mean-Square Error (RMSE) of RRIs.

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Graph-Based Denoising for Respiration and Heart Rate Estimation During Sleep in Thermal Video

Yang

Zhai

et al. 2022

IEEE Internet Things J.

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Overnight non-contact continuous vital signs monitoring using an intelligent automatic beam-steering Doppler sensor at 2.4 GHz

Cited by 3 publications

References 13 publications

A Review on Methods for Random Motion Detection and Compensation in Bio-Radar Systems

A Review on Methods for Random Motion Detection and Compensation in Bio-Radar Systems

Innovative non-contact r-r intervals estimation using viterbi algorithm with Squared Branch Metric (VSBM)

Graph-Based Denoising for Respiration and Heart Rate Estimation During Sleep in Thermal Video

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