A 2.4 GHz Bio-Radar System with Small Size and Improved Noise Performance Using Single Circular-Polarized Antenna and PLL

Jang, Byung-Jun; Park, Jae-Hyung; Yook, Jong Gwan; Moon, Junho; Lee, Kyoung Joung

doi:10.5515/kjkiees.2009.20.12.1325

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…In the past two decades other Doppler radar noncontact vital sign detection schemes have been reported under different environments for different applications [15][16][17][18]. A critical problem that has prevented these technologies from being widely used is the noise produced by random body motion.…”

Section: Introductionmentioning

confidence: 99%

Heart Rate Detection During Sleep Using a Flexible RF Resonator and Injection-Locked PLL Sensor

Kim

Seung-Hun

et al. 2015

IEEE Trans. Biomed. Eng.

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Novel nonintrusive technologies for wrist pulse detection have been developed and proposed as systems for sleep monitoring using three types of radio frequency (RF) sensors. The three types of RF sensors for heart rate measurement on wrist are a flexible RF single resonator, array resonators, and an injection-locked PLL resonator sensor. To verify the performance of the new RF systems, we compared heart rates between presleep time and postsleep onset time. Heart rates of ten subjects were measured using the RF systems during sleep. All three RF devices detected heart rates at 0.2 to 1 mm distance from the skin of the wrist over clothes made of cotton fabric. The wrist pulse signals of a flexible RF single resonator were consistent with the signals obtained by a portable piezoelectric transducer as a reference. Then, we confirmed that the heart rate after sleep onset time significantly decreased compared to before sleep. In conclusion, the RF system can be utilized as a noncontact nonintrusive method for measuring heart rates during sleep.

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Section: Introductionmentioning

confidence: 99%

Heart Rate Detection During Sleep Using a Flexible RF Resonator and Injection-Locked PLL Sensor

Kim

Seung-Hun

et al. 2015

IEEE Trans. Biomed. Eng.

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“…We have also introduced a circular polarized antenna to reduce size and to allow use of a single antenna for bio-radar applications [12,13]. In the present paper, a MIMO bio-radar system is introduced that consists of two bio-radar system sharing identical VCO with a PLL and new concept of direction finding of human target based on phase difference between two receivers is presented.…”

Section: -1 System Configurationmentioning

confidence: 99%

Detection of Human Vital Signs and Estimation of Direction of Arrival Using Multiple Doppler Radars

An¹,

Jang

Yook

2010

Journal of electromagnetic engineering and science

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This paper presents a non-contact measurement method of vital signal by the use of multiple-input multiple-output (MIMO) bio-radar system, configured with two antennas that are separated by a certain distance. The direction of arrival (DOA) estimation algorithm for coherent sources was applied to detect vital signals coming from different spatial angles. The proposed MIMO bio-radar system was composed of two identical transceivers sharing single VCO with a PLL. In order to verify the performance of the system, the DOA estimation experiment was completed with respect to the human target at angles varying between -50° and 50° where the bio-radar system was placed at distances (corresponding to 50 cm and 95 cm) in front of a human target. The proposed MIMO bio-radar system can successfully find the direction of a human target. Ⅰ. IntroductionRecently, remote sensing techniques have been actively studied as a means of measuring vital signs. Among these techniques, the Doppler radar sensing of vital signs has received substantial attention due to its simple system architecture and non-contact detection capability [1,2]. Various Doppler radar architectures for sensing human vital signs have consequently been developed: a Doppler radar system based on board-level and chip-level design [3], a dual-antenna Doppler radar system compensated for background motion [4], a barrier penetration consisted of ultra-wide band (UWB), and a CW Doppler radar [5] are some examples. MIMO signal processing methods, such as blind source separation (BSS) and analytical constant modulus algorithm (ACMA), have attracted a great deal of interest for non-contact vital sign detection [6,7]. Until recently, however, the existing MIMO techniques for vital sign detection have been mainly investigated to separate vital signs from multiple sources.The use of MIMO radar technique for vital signal sensing has a number of potential advantages. For a given system design choice, some of these advantages are enhancement of the target detection performance, improvement of the angle estimation accuracy, and a decrease in the minimum detection velocity [8]. A MIMO bio-radar system can also be combined with well-known direction of arrival (DOA) estimation algorithms to provide solutions for direction finding of human subjects. In the present paper, a new approach is presented to find the direction of human vital signals with two identical transceiver architectures sharing a single VCO with a PLL. The MIMO Doppler radar system can be effectively applied to find a human target with respect to azimuth angle, making it a good candidate for applications in home health care systems, military surveillance, as well as security services. To the best of authors' knowledge, this is the first successfully implemented direction finding system for human targets based on a MIMO radar concept. Ⅱ. MIMO Bio-Radar System ConfigurationThe configuration of the proposed integrated MIMO bioradar system is shown in Fig. 1. This monostatic MIMO radar consists of two antennas...

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Hand Gesture Classification Using Multiple Doppler Radar and Machine Learning

Baik¹,

Jang²

2017

J. Korean Inst. Electromagn. Eng. Sci.

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This paper suggests a hand gesture recognition technology to control smart devices using multiple Doppler radars and a support vector machine(SVM), which is one of the machine learning algorithms. Whereas single Doppler radar can recognize only simple hand gestures, multiple Doppler radar can recognize various and complex hand gestures by using various Doppler patterns as a function of time and each device. In addition, machine learning technology can enhance recognition accuracy. In order to determine the feasibility of the suggested technology, we implemented a test-bed using two Doppler radars, NI DAQ USB-6008, and MATLAB. Using this test-bed, we can successfully classify four hand gestures, which are Push, Pull, Right Slide, and Left Slide. Applying SVM machine learning algorithm, it was confirmed the high accuracy of the hand gesture recognition.

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A 2.4 GHz Bio-Radar System with Small Size and Improved Noise Performance Using Single Circular-Polarized Antenna and PLL

Cited by 6 publications

References 3 publications

Heart Rate Detection During Sleep Using a Flexible RF Resonator and Injection-Locked PLL Sensor

Heart Rate Detection During Sleep Using a Flexible RF Resonator and Injection-Locked PLL Sensor

Detection of Human Vital Signs and Estimation of Direction of Arrival Using Multiple Doppler Radars

Hand Gesture Classification Using Multiple Doppler Radar and Machine Learning

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