• International journal of advanced smart convergence
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• v.11 no.3
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• pp.179-186
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• 2022

In this paper, we design a heart rate measurement system using a web camera. In order to measure the heart rate, face image information is acquired and classified. The face image data is collected from web camera. The heart rate is measured using the collected face image data. We design a function to measure heart rate using input of face information using a web camera in non-contact manner. We design a function that reads face information and estimates heart rate by analyzing face color. An experiment was performed to compare the non-contact heart rate with the actual measured heart rate. The heart rate measurement system using a web camera proposed in this paper is a technology that can be used in various fields. It will be used in sports fields that require heart rate measurement at a low cost.

• Journal of Biomedical Engineering Research
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• v.31 no.2
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• pp.170-175
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• 2010

A method of measuring heart rate using photoplethysmograph(PPG) signal during exercise is proposed. PPG's are composed of strong base tones and their harmonics, and the strong base tones are trackable by the adaptive notch filter (ANF) which adjusts its coefficients to minimize the output power. The proposed heart rate measurement algorithm continuously notches the frequency component with the maximum power in the measured PPG, so that the fundamental frequency corresponding to heart rate is traced. We also presents methods of detecting degeneration and impulsive noise blocks to minimize the coefficient fluctuation. Experiments were conducted using real PPG signals captured during exercise. Results showed that the proposed algorithm is capable of consistently tracking the heart rate embedded in the noisy PPG's.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.1-10
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• 2021

Heart Rate is a crucial physiological parameter that provides basic information about the state of the human body in the cardiovascular system, as well as in medical diagnostics and fitness assessments. At present day, it has been demonstrated that facial video-based photoplethysmographic signal captured using a low-cost RGB camera is possible to retrieve remote heart rate. Traditional heart rate measurement is mostly obtained by direct contact with the human body, therefore, it can result inconvenient for long-term measurement due to the discomfort that it causes to the subject. In this paper, we propose a non-contact-based remote heart rate measuring approach of the subject which depends on the color intensity variation of the subject's facial skin. The proposed method is applied in two regions of the subject's face, forehead and cheeks. For this, three different algorithms are used to measure the heart rate. i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA). The average accuracy for the three algorithms utilizing the proposed method was 89.25% in both regions. It is also noteworthy that the FastICA algorithm showed a higher average accuracy of more than 92% in both regions. The proposed method obtained 1.94% higher average accuracy than the traditional method based on average color value.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.37-39
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• 2022

As the COVID-19 pandemic hits the world, the Tokyo Olympics in 2021 will be held behind closed doors. Some broadcasters showed the heart rate of the players in real time using image processing-based non-contact measurement to convey the vividness of the scene on TV. However, since the non-contact model uses changes in the skin color of the players' faces according to blood circulation as a parameter, there is a possibility that errors may occur due to interference factors such as natural light or glasses. Therefore, in this paper, the non-contact heart rate measurement model and the contact heart rate measurement model are tested in an environment free from interference and their accuracy is analyzed.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.87-93
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• 2017

In this paper, we design a small low power single channel ECG(Electrocardiogram) system of Chest Belt type with fiber-type electrodes to measure emotional state change of game addict. HRV(Heart Rate Variability) is analyzed through heart rate signal measurement and the psychological stress state is judged by using it. And it verifies its effectiveness through prototype. First, we design HR measurement module through low power MCU(Micro Controller Unit) and implement prototype level measurement system. The results showed that the difference between the addiction group and the general group was confirmed and that the system was effective. The result of this study can be used for health management such as reduction of stress of the user through music and breathing that lowers the stress by detecting the stress state of the general person or the chronic ill person.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1388-1395
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• 2020

Daily monitoring of the heart rate can facilitate detection of heart-related diseases in their early stages. Therefore, providing an easy-to-use and noninvasive heart rate monitoring system has been a very popular research topic in the field of healthcare. One of good candidate methods is to use commonly available cameras and extract information that can help to estimate heart rate from a human face. Generally, such information can be retrieved using two different approaches: photoplethysmography (PPG) and ballistocardiography (BCG). PPG exploits slight color changes caused by blood volume variations during heartbeats; thus, it tends to be vulnerable to unstable lighting conditions. BCG exploits subtle head motions caused by pumped blood travelling through the carotid artery during heartbeats; thus, it is vulnerable to the voluntary head movements that are not related to heartbeats. Nevertheless, most related works use either to estimate the heart rate. In this paper, we propose to combine two approaches to be robust to challenging conditions. Specifically, we explore possible ways to combine raw signals obtained from two approaches and verify that the proposed combination shows better accuracies under challenging conditions, such as voluntary head movements and ambient lighting changes.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.363-369
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• 2023

In this study, to check the function of managing the severity of ultraviolet rays with a smart watch, a popular health care IT device, It was tested whether measuring heart rate using a PPG(Photoplethysmography) sensor representatively used in a smart watch could tell skin changes caused by ultraviolet rays. Through this experiment, we examined the possibility that the skin color tanned by ultraviolet rays can be determined only by the heart rate measurement function of the PPG sensor. In addition, the possibility of expanding the heart rate measurement function of the PPG sensor to the use of skin condition management was considered. we used an Arduino-based reflective PPG sensor to measure changes in heart rate by selecting body sites with high and low UV rays exposure. A significant value was derived through tests considering factors such as gender, UV exposure, and age. As a result, the study identified the possibility of adding ultraviolet rays and skincare items to future smart watch healthcare items and the possibility of expanding skin measurement methods. It is also possible to suggest the direction of future research.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.33-37
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• 2024

Recently, wearable virtual reality devices are widely used. These instruments include a 3-axis accelerometer. User's heart rate information in virtual reality contents can be useful for measuring user experience. In this paper, we propose a method to measure the heart rate through a 3-axis accelerometer based on the principle of ballistocardiography without additional sensors. The angular velocity was successively measured in a time series by the 3-axis accelerometer mounted to the head. The frequency of the maximum magnitude is determined as the heart rate through frequency transform and band pass filtering of the time series signal. For verification, the heart rate calculated from photoplethysmography sensors acquired at the same time was compared as ground-truth. In the virtual reality, the user's heart rate information can be extracted without additional heart rate sensor, and the emotional state and fatigue can be measured.

• Korean Journal of Radiology
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• v.20 no.1
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• pp.94-101
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• 2019

Objective: To investigate the efficacy of motion-correction algorithm (MCA) in improving coronary artery image quality and measurement accuracy using an anthropomorphic dynamic heart phantom and 256-detector row computed tomography (CT) scanner. Materials and Methods: An anthropomorphic dynamic heart phantom was scanned under a static condition and under heart rate (HR) simulation of 50-120 beats per minute (bpm), and the obtained images were reconstructed using conventional algorithm (CA) and MCA. We compared the subjective image quality of coronary arteries using a four-point scale (1, excellent; 2, good; 3, fair; 4, poor) and measurement accuracy using measurement errors of the minimal luminal diameter (MLD) and minimal luminal area (MLA). Results: Compared with CA, MCA significantly improved the subjective image quality at HRs of 110 bpm (1.3 ± 0.3 vs. 1.9 ± 0.8, p = 0.003) and 120 bpm (1.7 ± 0.7 vs. 2.3 ± 0.6, p = 0.006). The measurement error of MLD significantly decreased on using MCA at 110 bpm (11.7 ± 5.9% vs. 18.4 ± 9.4%, p = 0.013) and 120 bpm (10.0 ± 7.3% vs. 25.0 ± 16.5%, p = 0.013). The measurement error of the MLA was also reduced using MCA at 110 bpm (19.2 ± 28.1% vs. 26.4 ± 21.6%, p = 0.028) and 120 bpm (17.9 ± 17.7% vs. 34.8 ± 19.6%, p = 0.018). Conclusion: Motion-correction algorithm can improve the coronary artery image quality and measurement accuracy at a high HR using an anthropomorphic dynamic heart phantom and 256-detector row CT scanner.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1481-1491
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• 2021

Since most biosignals rely on contact-based measurement, there is still a problem in that it is hard to provide convenience to users by applying them to daily life. In this paper, we present a mobile application for estimating heart rate based on a deep learning model. The proposed application measures heart rate by capturing real-time face images in a non-contact manner. We trained a three-dimensional convolutional neural network to predict photoplethysmography (PPG) from face images. The face images used for training were taken in various movements and situations. To evaluate the performance of the proposed system, we used a pulse oximeter to measure a ground truth PPG. As a result, the deviation of the calculated root means square error between the heart rate from remote PPG measured by the proposed system and the heart rate from the ground truth was about 1.14, showing no significant difference. Our findings suggest that heart rate measurement by mobile applications is accurate enough to help manage health during daily life.