• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.5
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• pp.284-288
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• 2016

Among the various physiological information that could be obtained from human body, heartbeat rate is a commonly used vital sign in the clinical milieu. Photoplethysography (PPG) sensor is incorporated into many wearable healthcare devices because of its advantages such as simplicity of hardware structure and low-cost. However, healthcare device employing PPG sensor has been issued in susceptibility of light and motion artifact. In this paper, to develop the real-time heart rate measurement device that is less sensitive to the external noises, we have fabricated an ultra-small wireless LC resonant pressure sensor by MEMS process. After performance evaluation in linearity and repeatability of the MEMS pressure sensor, heartbeat waveform and rate on radial artery were obtained by using resonant frequency-pressure conversion method. The measured data using the proposed heartbeat rate measurement system was validated by comparing it with the data of an commercialized heart rate measurement device. Result of the proposed device was agreed well to that of the commercialized device. The obtained real time heartbeat wave and rate were displayed on personal mobile system by bluetooth communication.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2057-2061
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• 2008

Individual heartbeat has specific character by a condition of heart, structure, age, and so forth. On this paper, We propose that individual verification method using specific character of heartbeat. This character are obtained by measure PPG(Photo Plethysmogram) using LD and PD.

• Journal of Biomedical Engineering Research
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• v.38 no.5
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• pp.264-270
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• 2017

A Doppler radar sensor was applied to detect respirations and heartbeats of persons who were lying on a bed. This study is preliminary study aiming at non-contact and non-intrusive respiration and heart rate monitoring during sleep in daily life. For the experiments, 10GHz Doppler radar with patch-type antenna was used and installed on the upper right and the distance between the body and the antenna was 1 m. The results show that each signal of respiration and heartbeat is observed in each frequency band however the frequency band and the waveform vary according to the subjects and the posture. The results show that the heartbeats can be detected with the peak detection in some frequency band. This study shows the feasibility of applying the Doppler radar to detection of heartbeat and respiration during sleep and further studies about heartbeat detection algorithm are required.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.63-69
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• 2020

In this paper, a small microwave sensor that can be applied to a wearable device is proposed because it can detect the heartbeat signal of a human body moving irregularly at low speed. It consist of balanced microstrip radiation patches in the 2.4 GHz ISM band, self-oscillation detection circuit, and feedback circuit. Based on the theoretical development and simulation, the validity of the proposed structure was confirmed and the manufactured prototype was tested. The board size of the circuit is as small as 65mm × 85㎟, and has a low power consumption of 60mW thanks to the simple RF circuit structure. Finally heartbeat signal has been obtained from a human body moving at low speed (0.5Hz) within a linear distance of 2 to 30mm close to the sensor and a lateral distance of ±20mm.

• Journal of Computing Science and Engineering
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• v.8 no.1
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• pp.17-24
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• 2014

In this paper, we propose a new implementation of a failure detector. The implementation uses a dual model of heartbeat and interaction. First, the heartbeat model is adopted to shorten the detection time, if the detection process does not receive the heartbeat message in the expected time. The interaction model is then used to check the process further. The expected time is calculated using the exponential smoothing method. Exponential smoothing can be used to estimate the next arrival time not only in the random data, but also in the data of linear trends. It is proven that the new detector in the paper can eventually be a perfect detector.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.91-102
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• 2017

Many of the wearable smart fitness devices provide services related to users' heartbeat rates. These services use fixed standards which have been pre-determined based on statistical data. However, because body conditions significantly differ between individuals, the services applying fixed standards to all individuals are not reliable. This paper proposes the Feedback-RFC model which adapts heartbeat standards to individual users' exercise abilities and also proposes a method to implement the model. This paper also shows the effectiveness of the Feedback-RFC model by collecting heartbeat data from 12 participants and evaluating the model with the data.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.51-56
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• 2019

This paper proposes an improved heartbeat signal extraction method for ballistocardiography(BCG)-based heart-rate measurement on mobile environment. First, from a mobile facial video, a handshake-free head motion signal is extracted by tracking facial features and background features at the same time. Then, a novel signal periodicity computation method is proposed to accurately separate out the heartbeat signal from the head motion signal. The proposed method could robustly extract heartbeat signals from mobile facial videos, and enabled more accurate heart rate measurement (measurement errors were reduced by 3-4 bpm) compared to the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.70-76
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• 2019

Ultra Wideband (UWB) Radar is a high-resolution radar for short distance detection which uses signals transmitted and received by each antennas in order to detect a target. It is possible to detect the respiration and heartbeat of a person without contact It is getting more and more often utilized since it is not affected by physical environment. In this paper, we implement an algorithm to detect human respiration and heartbeat rate using UWB radar signal. We process radar signals reflected from human body using Median filter, Kalman filter, Band Pass filter and so on. We also use CZT to extract breathing and heart rate. ECG (Electrocardiogram) was used for comparison of heartbeat data and we confirm that each data of ECG and UWB Radar were more than 98% identical each other.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.25-31
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• 2005

We know that the Hurst Exponent (HE) is a real number in [0, 1] which denotes randomness of time series. in this research, we suggest non-linear analysis of human biological signals through HE. The feasibility of human biological signals using inductive incitement provides Some diagnosis for active treatment. In our experiment, we measured the heartbeat through the MCG, 29 healthy and 34 abnormal subjects ostensibly. The raw data of acupuncture incitement are supported by opinions of gross examination and pathological diagnosis. The mean values of HE are 0.345, 0.755 and 0.805 for the periods of before, during and after acupuncture treatment, respectively in case of abnormal subjects. On the other hand, the mean values, 0.808, 0.797 and 0.785 are for normal cases, correspondingly. From this data, we show that HE is very significant in abnormal controls according to an acupuncture incitement, and the incitement effect is evidently extracted in abnormal subjects. But, in normal subjects, the incitement effect is meaningless.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.119-122
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• 2008

Individual heartbeat has specific character by a condition of heart, structure, age, and so forth. On this paper, We propose that individual verification method using specific character of heartbeat. This character are obtained by measure PPG(Photo Plethysmogram) using LD and PD.