• Journal of Biomedical Engineering Research
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• v.44 no.1
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• pp.80-84
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• 2023

Electrodes are one of the types of biosensors capable of measuring bio signals, such as electrocardiogram (ECG) and electromyogram (EMG) signals. These electrodes are used in various fields and offer the advantage of being able to measure ECG signals without the need for skin attachment, compared to Ag/AgCl electrodes. The purpose of this study was to evaluate the efficacy of conductive textile electrodes in collecting ECG signals in a bed-like environment. Three adult participants were involved, and a total of 30 minutes of ECG signals were collected for each participant. The collected ECG signals were analyzed to determine the heart rate, normLF and a comparison was made between the conductive textile electrodes and Ag/AgCl electrodes. As a result, the change in heart rate and normLF could be observed, and in particular, the difference between the two electrodes decreased. This study confirmed that conductive textile electrodes can effectively collect ECG signals in a bed-like environment. It is hoped that this research will lead to the development of a system that can detect various sleep-related diseases through the use of these electrodes.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.175-182
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• 1995

Despite the simplicity of processing, a conventional autocorrelation function (ACF) method for the precise determination of fetal heart rate (FHR) has many problems. In case of weak or noise corrupted Doppler ultrasound signal, the ACF method is very sensitive to the threshold level and data window length. It is very troublesome to extract FHR when there is a data loss. To overcome these problems, the high resolution pitch detection algorithm was adopted to estimate the FHR. This method is more accurate, robust and reliable than the ACF method. With a lot of calculation, however, it is impossible to process real time FHR estimation. This paper is presented a new FHR estimation algorithm for real time processing and studied the real time FHR monitoring system by high resolution pitch detection algorithm.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.137-142
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• 2019

This paper Various services exist to detect and monitor abnormal event. However, most services focus on fires and gas leaks. so It is impossible to prevent and respond to emergency situations for the elderly and severely disabled people living alone. In this study, AI model is designed and compared to detect abnormal event of heart rate signal which is considered to be the most important among various bio signals. Specifically, electrocardiogram (ECG) data is collected using Physionet's MIT-BIH Arrhythmia Database, an open medical data. The collected data is transformed in different ways. We then compare the trained AI model with the modified and ECG data.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.105-111
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• 2012

Photoplethysmogram is widely used to measure heart rate and arterial blood oxygen saturation in human. This paper describes implementation a photoplethysmography monitoring system that uses 780nm and 940nm length infrared light in radial artery. That system used combinations of 8 LEDs and 2 photoelectricities. When recorded on the skin over radial artery, the radial pulse wave was inverted. The mechanism of inverted pulse wave skin, which was reduced during systolic period and increase during diastolic period of the cardiac cycle. Through this system, we discovered optimal environments and combinations of sensors in both penetration type and reflection type. These results suggest that radial arterial wall way reflect infrared ray.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2080-2085
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• 2018

There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.2
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• pp.50-55
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• 2015

The noise of MRI shooting is 100dB loud and has an intensive psychological and physiological influences on the human body. ECG signals were measured by experimental methods, while wearing earplugs for 15 minutes in the stable state. Then the ECG signals were measured for 30 minutes while listening to about 100dB of sound in a MRI equipment. In this study, the heart rate variability of men and women was analyzed according to the MRI noise stress level through the frequency analysis. As the MRI noise level is about 100dB, HRV analysis resulted in an imbalance between the sympathetic and parasympathetic. During the period from the resting state up to 10 minutes, the maximum stress state was shown. This study will encourage MRI workers to take interests in hearing protection for the patient and to make objective indicators about MRI noises.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.31-37
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• 2010

This study was developed the home network system for the home stay care by bio-sensor system to translate the physical signal algorithm. The composition algorithm has five functions for a input function, frequency variable, displacement point input function, axial Variable, axial Sway Displacement to search a max and min point with adjustment of 0.01 unit in the reference level. There were checked physical condition of body balance to compounded a measurement such as a heart rate, temperature, weight. The algorithm of home network system can be used to support health care management system through health assistants in health care center and central health care system. It was expected to monitor a physical parameter for health management system.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.117-124
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• 2011

This study was realized the home network system for home care by bio-physical sensor system, to convey for the remote physical signal. The composition condition has four functions of displacement point for a Vision, Somatosensory, Vestibular and CNS that the basic measurement used to a Heart Rate, Temperature, Weight. Physical signal are decided to search a max and min point with adjustment of 0.01 unit in the reference level. There were checked physical condition of body balance to compounded a physical neuroceptor of sensory organ for the measurement such as a Vision, Somatosensory, Vestibular, CNS, BMI. There are to check a health care condition through a combination of physical organ with a posturography of a exercise. The service of home network system can be used to support health care management system through health assistants in health care center and central health care system. It was expected to monitor a physical parameter for the remote control health management system.

• 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 Korean Society of Radiology
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• v.16 no.5
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• pp.545-551
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• 2022

This study analyzed the correlation between stress measurements calculated through HRV signals and thyroid function test items. 181 healthy adults without disease who visited Clinic K were the subjects of this study. Stress resistance (SR) and stress index (SI) were calculated using the acquired HRV signal, and TSH, Free T4, and T3 were used as thyroid function test items. For the measured values, the relationship between each item was statistically analyzed through Pearson correlation analysis. From the results, it was confirmed that Free T4 and SR had a positive correlation (r=0.18) and a negative correlation with SI (r=-0.16). Through this, it was confirmed that there is a significant relationship between thyroid function and HRV signal.