• 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 Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.82-87
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• 2016

The photoplethysmogram (PPG) signal is one of the mainly considered bio signals along with the electrocardiogram (ECG) signal. PPG signals can be used to estimate the speed of flow of blood in vein, saturation of peripheral oxygen and etc. The heartbeat rate is a common feature in order to evaluate those checkup lists. To estimate the correct heartbeat rate, dynamic noises must be removed in the PPG signal. Conventionally, the acceleration signal is used to remove dynamic noises. This method, however, increases the computational complexity. In this paper, we proposes a solution that uses only PPG signals to calculate the heartbeat rate, and which can be used as a basement in real-time healthcare solution.

• 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 the Korean Society of Manufacturing Process Engineers
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• v.18 no.4
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• pp.100-108
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• 2019

In this paper, a new stacked element pressure sensor has proposed for heartbeat and respiration measurement. This device can be directly attached to an individual's chest; heartbeat and respiration are detected by the pulsatile vibration and deformation of the chest. A key feature of the device is the simultaneous measurement of heart rate and respiration. The structure of the sensor consists of two stacked elements, in which one element includes one polyvinylidene fluoride (PVDF) thin film bonded on polydimethylsiloxane (PDMS) substrate. In addition, for the measurement and signal processing, the electric circuit and the filter are simply constructed with an OP-amp, resistance, and a capacitor. One element (element1, PDMS) maximizes the respiration signal; the other (element2, PVDF) is used to measure heartbeat. Element1 and element2 had sensitivity of 0.163V/N and 0.209V/N, respectively, and element2 showed improved characteristics compared with element1 in response to force. Thus, element1 and element2 were optimized for measuring respiration heart rate, respectively. Through mechanical and vivo human tests, this sensor shows the great potential to optimize the signals of heartbeat and respiration compared with commercial devices. Moreover, the proposed sensor is flexible, light weight, and low cost. All of these characteristics illustrate an effective piezoelectric pressure sensor for heartbeat and respiration measurements.

• 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 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 Environmental Science International
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• v.16 no.1
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• pp.55-63
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• 2007

There are concerns that chemical residues could harm the consumer on the environment, although 50 to 80% of the crops would be destroyed by pests and others without agrochemicals. Environmental fate and ecotoxicity studies are usually carried out to assess the impact on the human and the environment. A comparision of the Daphnia magnia and Simocephalus mixtus toxicity was performed to study the relative sensitivities and discrimination abilities to agriculture chemicals. The species of Simocephalus mixtus was more sensitive to agriculture chemicals than Daphnia magnia. Simocephalus mixtus was approved to be a water flea in determining insecticide and pesticide toxicity by heart-beat rate in a consistency and repeatability. The order of acute toxicity to water flea Daphnia magnia for ecotoxicity test was carbaryl>benomyl>amtirole with both Daphnia magnia and Simocephalus mixtus. The heartbeat pattern after the exposure to agrochemicals was different from that of exposure to heavy metals. Agrochemical leathal concentration test with heartbeat rate measurement was found to be more appropriate than inhibition concentration test with respect to toxicological endpoint.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.83-88
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• 2017

The personal activity information is expanding as a way to utilize wearable devices that are emerging as next generation smart devices. This paper develops an application for collecting heartbeat rate and location information of a user using SmartWatch, which is a smartphone and wearable device, and analyzing it through machine learning to infer user's emotion information. By using smart phone and smart watch, developed application can collect biometric data and location information by simply executing application and doing everyday life. In addition, adding the location information to the hearbit rate data, it proves higher utilization than existing ones.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.25-32
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• 2022

IR-UWB radar has been regarded as the most promising technology for non-contact respiration and heartbeat monitoring because of its ability of detecting slight motion even in submillimeter range. Measuring heart rate is most challenging since the chest movement by heartbeat is quite subtle and easily interfered with by a random body motion or background noise. Additionally, periodic sampling can be limited by the performance of computer that handles the radar signals. In this paper, we deploy Lomb-Scargle periodogram method that estimates heart rate even with irregularly sampled data and uneven signal amplitude. Lomb-Scargle periodogram is known as a method for finding periodicity in irregularly-sampled and noisy data set. We also implement a motion detection scheme in order to make the heart rate estimation pause when a random motion is detected. Our scheme is implemented using Novelda's X4M03 radar development kit and its corresponding drivers and Python packages. Experimental results show that the estimation with Lomb-Scargle periodogram yield more accurate heart rate than the method of measuring peak-to-peak distance.

• Journal of Korea Multimedia Society
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• v.20 no.3
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• pp.465-473
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• 2017

Electrocardiogram(ECG) signal is one of the unique bio-signals of individuals and is used for personal authentication. The existing studies on personal authentication method using ECG signals show a high detection rate for a small group of candidates, but a low detection rate and increased execution time for a large group of candidates. In this paper, we propose a hierarchical algorithm that extracts fiducial points based on curvature of ECG signals as feature values for grouping candidates ​and identifies candidates using waveform-based comparisons. As a result of experiments on 74 ECG signal records of QT-DB provided by Physionet, the detection rate was about 97% at 3-heartbeat input and about 99% at 5-heartbeat input. The average execution time was 22.4 milliseconds. In conclusion, the proposed method improves the detection rate by the hierarchical personal authentication process, and also shows reduced amount of computation which is plausible in real-time personal authentication usage in the future.