• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.19-22
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• 2002

In this paper, we aims to develop a microcontroll er-based ECG monitoring system and portable pulse oximeter using Compact Flash Interface. First, portable pulse oximeter system is designed to record 2 channel of biosignals simultaneously, including 1 channel of $SpO_2$ and 1 channel of pulse rate. It is very small and portable. Besides, the system makes it possible to measure a patient's condition without an additional medical equipment. We tried to solve the problems generated by a patient's motion. That is, we added an analog circuit to a traditional pulse oximeter in order to eliminate the change of the base line. And we used 2D sector algorithm. As present, SpO2 modules are completed. But there are still many further development needed in order to enhance the function. Especially, compact falsh interface remains the most to complete. Second, ECG monitoring system uses almost same as present 3-lead ECG system. But we focus on the analog part, especially in filter. The proposed filter is composed of two parts. One is a filter to remove the power-line interface. The other is a filter to remove the baseline drift. A filter to remove the power-line and the baseline drift is necessarily used in the ECG system. The implemented filter have three features; minimizing the distortion in DC component, removing the harmonic component of power-line frequency. Using compact flash interface, we can easily transfer a patient's personal information and the measured signal data to a network based server environment. That means, it is possible to implement a patient's monitoring system with low cost.

• Journal of Biomedical Engineering Research
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• v.23 no.6
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• pp.485-489
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• 2002

In this study. respiratory efforts were monitored by the change of pulse transit time (PTT) which is related with the arterial pressure PTT is the time interval between the peak of R wave in ECG and the maximal slope point of photoplethysmogram(PPG). Biosignals, ECG and finger photoplethysmogram(PPG), were converted to digital data, and PTT was evaluated in personal computer with every heart beat. Results were presented as a graph using spline interpolation. The software was implemented in C$\^$++/ as a window-based application program. PTT was periodically changed according to airflow in resting respiration. In the resting respiration, PTT was changed according to the respiratory cycle. The amplitude of PTT fluctuation was increased by deep respiration, and increased by partial airway obstruction. These results suggest that PTT is responsible to respiratory effort which could be evaluated by the pattern of PTT change. And it is expected that PTT could be applied in the monitoring of respiratory effort by noninvasive methods, and is very useful method for the evaluation of respiratory distress.

• Journal of Advanced Navigation Technology
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• v.24 no.4
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• pp.322-327
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• 2020

Recently, a research on obtaining a vital signal using a Doppler radar has been developed and is used as a technology applied to patients in bed. However, in the case of the measured pulse, the respiration signal is generated as noise, resulting in a problem of lowering accuracy. In this paper, we propose a bio-signal measurement algorithm based on the sampling point to improve the accuracy of the signal for measuring the pulse rate when measuring bio-signals using a Doppler radar. The proposed algorithm improves the accuracy of the measured bio-signal by removing noise generated when measuring biosignals based on two sampling points. Compared with actual medical equipment and existing bio-signal algorithms, it is more than 90% similar to medical equipment. In addition, it was confirmed that severe amplitude change was minimized compared to the existing algorithm.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.107-115
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• 2021

Purpose: The aim of this study is to find the location of acupoints that are effective for increasing parasympathetic nervous system(PNS) activity among acupoints used to relieve symptoms such as dizziness and nausea. Materials and Methods: Twenty healthy adult men participated in this experiment. Transcutaneous electrical nerve stimulation(TENS) was applied to P6(Neiguan), ST36(Zusanli) and BL20(Pishu) for 30 minutes. For 5 minutes before and after stimulation, Electrocardiogram(ECG), Electrodermal activity(EDA), Respiration, and Skin temperature(SKT) were measured using biosignalsplux Professional(biosignalsplux; Portugal). Paired t-test was performed for the results before and after stimulation, and a one-way ANOVA test between stimulations was performed for the rate of change before and after stimulation. Results: When each acupoint was stimulated with TENS, it was found that the PNS was generally activated. In addition, when considering the change in biosignals after stimulation, the participants stimulated with P6 showed the most consistent results. Conclusion: As a result of stimulating each acupoint, it was found that stimulating P6 can effectively increase PNS activity. These results indicate that methods of stimulating P6 may be most effective in alleviating symptoms of motion sickness.

• 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.

• Journal of Digital Policy
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• v.1 no.2
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• pp.61-69
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• 2022

The paper is a study to develop and verify a blood glucose level prediction model based on biosignals obtained from photoplethysmography (PPG) sensors, ICT technology and data. Blood glucose prediction used the MLP architecture of machine learning. The input layer of the machine learning model consists of 10 input nodes and 5 hidden layers: heart rate, heart rate variability, age, gender, VLF, LF, HF, SDNN, RMSSD, and PNN50. The results of the predictive model are MSE=0.0724, MAE=1.1022 and RMSE=1.0285, and the coefficient of determination (R²) is 0.9985. A blood glucose prediction model using bio-signal data collected from digital devices and machine learning was established and verified. If research to standardize and increase accuracy of machine learning datasets for various digital devices continues, it could be an alternative method for individual blood glucose management.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.749-754
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• 2022

High adhesion and water resistance of the skin surface are required for wearable and skin-attachable electronic patches in various medical applications. In this study, we report a stretchable electronic patch that mimics the drainable structure pattern of the hexagonal channels of frog's pads and the sucker of an octopus based on carbon-based conductive polymer composite materials. The hexagonal channel structure that mimics the pads of frogs drains water and improves adhesion through crack arresting effect, and the suction structure that mimics an octopus sucker shows high adhesion on wet surfaces. In addition, the high-adhesive electronic patch has excellent adhesion to various surfaces such as silicone wafer (max. 4.06 N/cm²) and skin replica surface (max. 1.84 N/cm²) in dry and wet conditions. The high skin-adhesive electronic patch made of a polymer composite material based on a polymer matrix and carbon particles can reliably detect electrocardiogram (ECG) in dry and humid environments. The proposed electronic patch presents potential applications for wearable and skin-attachable electronic devices for detecting various biosignals.

• Journal of Biomedical Engineering Research
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• v.44 no.4
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• pp.284-292
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• 2023

This study attempted to observe muscle activity and muscle fatigue among isotonic exercise of Biceps Brachii and Deltoidus Medius, which correspond to upper limb muscles, using metronome. For the experiment, 13 adult men participated to evaluate biosignals (ECG, EMG). For quantitative evaluation, 1RM and MVIC test were carried out and a constant pace isotonic excise session was conducted. Five sets of exercise were performed, and each set proceeded to the failure point while the speed condition (30bpm) was assigned. As a result of the experiment, muscle activity in both muscles was significantly reduced in fifth set compared to first set. Muscle fatigue has been confirmed to occur at a significant level within the set, but there was only a significant difference in both muscles in the first and second sets between sets. This is similar to the results of previous studies that gives the same rest time(2min), but further research is needed to see if the conditions for the number of repetitions are affected. Based on the recent increase of interest in muscle strength exercise, this study was conducted to observe the results by varying the conditions of common exercise.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.62-69
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• 2022

An electrocardiogram (ECG) is one of the most important biosignals, and in particular, continuous ECG monitoring is very important in patients with arrhythmia. There are many different types of arrhythmia (sinus node, sinus tachycardia, atrial premature beat (APB), and ventricular fibrillation) depending on the cause, and continuous ECG monitoring during daily life is very important for early diagnosis of arrhythmias and setting treatment directions. The ECG signal of arrhythmia patients is very unstable, and it is difficult to detect the R-peak point, which is a key feature for automatic arrhythmias detection. In this study, we develped a continuous measuring Holter ECG monitoring device and software for analysis and confirmed the utility of R-peak of the ECG signal with MIT-BIH arrhythmia database. In future studies, it needs the validation of algorithms and clinical data for morphological classification and prediction of arrhythmias due to various etiologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.208-210
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• 2021

As the number of objects connected to the Internet increases rapidly, intelligent device development projects are gradually expanding that provide direct value to humans, away from simple monitoring functions, including sensors and communication functions, or delivery to servers.It is expected that the device will develop a technology that analyzes surrounding sensing information and changes the surrounding environment in consideration of users' preferences or safety. By establishing a biosignal measurement system in a developed product that can bring various effects using air, it will be possible to grasp the user's condition through a pattern of change in pressure distribution when seated. This paper proposes a construction system that enhances the comfort of using an air car seat through contact between a temperature measurement sensor and a user, and enables effective management of measured biosignals by linking them with an air pump control system.