• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.53-58
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• 2019

Recently, product research has been continuously conducted to enhance accessibility to blood pressure measurement for the purpose of healthcare for the chronic patient. In previous studies, electrocardiogram (ECG) and photoelectric pulse wave (PPG) are analyzed to calculate systolic and diastolic blood pressure. The problem is the development of analysis algorithms for accuracy and reproducibility. In this study, in the development stage of a micro blood pressure measuring device, the size of the device was reduced and the measurement method was simplified, while the algorithm was to extract systolic blood pressure (SBP) using only two PPGs and obtain diastolic blood pressure (DBP). The difference value of PPG, DF_P, is inversely related to SBP, and has a proportional relationship with DBP, which can be leaked by algorithm, and DBP can be tracked through SBP.

• 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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.232-235
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• 2009

본 연구에서는 실시간으로 변화하는 사용자의 감성을 평가하여 각성 또는 이완으로 분류된 시선 정보 이미지를 저장하는 시스템을 구현하고자 한다. 사용자의 감성을 분류하기 위한 요소는 Larson과 Diner 가 정의한 2 차원 감성모델에서 각성, 이완 요소를 사용한다. 감성 상태를 분류하기 위하여 자율 신경계 중 착용과 휴대가 간편한 PPG 센서를 사용하며, PPG 를 분석하기 위한 변수로는 진폭의 양과 초당 Peak 의 빈도수를 사용한다. 머리에 고정할 수 있는 캠을 사용하여 사용자가 바라보는 시선 정보를 획득하고, 클라이언트 컴퓨터는 획득된 시선 정보를 UDP 통신을 사용해 서버 컴퓨터로 전송하는 시스템이다. 320(pixel)*240(pixel)*32(bit)인 영상 데이터를 1/30 로 압축하여 전송하며, 각성과 이완으로 분류되는 시점의 영상을 블록화하여 JPEG 이미지로 저장한다. 본 시스템은 실시간으로 변화되는 사용자의 감성 상태를 파악하여 이미지를 전송하고 서버 컴퓨터에 저장함으로써 당시 사용자가 느꼈던 감성들에 대해 피드백을 주고자 하는데 의의가 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.115-117
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• 2013

본 논문에서는 660nm 파장의 적색광과 940nm 파장의 적외선을 활용한 광전용적맥파(photoplethysmo graphy:PPG)를 기반으로 한 산소포화도 측정에 대하여 연구하였다. 본 논문에서는 기존의 한 손가락에서 서로 다른 두 파장의 광(光)을 번갈아 켜고 끄며 측정하던 산소포화도 측정방식과 달리 서로 다른 두 파장의 광을 각각 서로 다른 손가락에서 측정 한 후 각각의 광전용적맥파를 통하여 산소포화도를 측정할 수 있는 방법을 제안하였다. 이 방법은 동시에 한곳에서 측정할 때와 달리 서로 다른 두광을 Switching할 필요 없이 동시에 측정 가능하며 이를 통하여 서로 다른 곳에서 측정한 광전용적맥파를 이용하여 산소포화도 측정이 가능하다는 결론을 얻었다.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.701-706
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• 2007

The measurement accuracy for heart rate or $SpO_2$ using photoplethysmography (PPG) is influenced by how well the noise from motion artifacts and other sources can be removed. Eliminating the motion artifacts is particularly difficult since its frequency band overlaps that of the basic PPG signal. Therefore, we propose the Periodic Moving Average Filter (PMAF) to remove motion artifacts. The PMAF is based on the quasi-periodicity of the PPG signals. After segmenting the PPG signal on periodic boundaries, we average the $m^{th}$ samples of each period. As a result, we remove the motion artifacts well without the deterioration of the characteristic point.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.4
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• pp.499-508
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• 2014

In this paper, we implemented a LED sensitivity illumination system, being driven in response to changes in the biological signals of GSR and PPG signal. After measuring biological signals of a human body from GSR and PPG sensor modules, MCU decided the state of relaxation or arousal of the subject, being based on the wake relaxation identifying map proposed in this paper. A developed LED sensitivity illumination system makes the subject to reach a normal state by giving a change of the LED illumination color, corresponding to a state of the subject.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.5
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• pp.675-679
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• 2018

A novel heart rate estimation algorithm is presented based on normalized least-mean-square (NLMS) algorithm. This paper presented a three-step processing scheme for estimating heart rate from PPG signal with motion artifacts. The proposed active noise cancellation algorithm has low computational complexity compared to the NLMS algorithm. Experimental results show that the proposed algorithms perform similar with the previous algorithm under motion artifact noises.

• Journal of Biomedical Engineering Research
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• v.35 no.6
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• pp.197-202
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• 2014

The cognitive rehabilitation training is important for treating many cognitive impairment conditions, including Parkinson's disease, stroke, and ADHD. In this study, we developed a new evaluation system to improve the measurement of the conventional evaluation systems for cognitive rehabilitation training. The developed system measured the activity of dopamine(DA) and an autonomic nervous system(ANS) with photoplethysmography and electromyography. The results demonstrated that the cognitive capacity was increased but the activity of DA was decreased with unbalanced ANS by short-term stress. Based on the results, the effect of short-term stress should be recognized for the cognitive rehabilitation training.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.91-95
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• 2012

The photoplethysmography (PPG) signal measured from a mobile healthcare device contains various motion artifacts occurring from a patient’s movements. Recently, to reject the motion artifacts, the method of using an acceleration sensor was suggested, but such sensors are very expensive. Therefore, this study deals with a novel sensor device to replace the acceleration sensor, and evaluated the performance of the proposed sensor experimentally. In the results of the experiments, it is shown that the proposed sensor device can reconstruct the PPG signal despite the occurrence of motion artifacts, and also that the variation rate in heart rate analysis was 1.22%. According to the experimental results, the proposed method can be applied to design a low-cost device.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.138-142
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• 2017

Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. In this paper, we described the implementation heart rate monitoring system using PPG sensor. Proposed system is collected data using PPG sensor and heart rate was detected using second derivative method. In order to verify the effectiveness of the proposed method, we performed the measurements of RR-intervals with a commercial medical device.