• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.576-583
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• 2008

In this study, we attempt to design a real-time autonomic nervous system(ANS) evaluation system usable during exercise using heart instantaneous frequency(HIF). Although heart rate variability(HRV) is considered to be a representative signal widely used ANS evaluation system, the R-peak detection process must be included to obtain an HRV signal, which involves a high sampling frequency and interpolation process. In particular, it cannot accurately evaluate the ANS using HRV signals during exercise because it is difficult to detect the R-peak of electrocardiogram(ECG) signals with exposure to many noises during exercise. Therefore, in this study, we develop the ground for a system that can analyze an ANS in real-time by using the HIF signal circumventing the problem of the HRV signal during exercise. First, we compare the HRV and HIF signals in order to prove that the HIF signal is more efficient for ANS analysis than HRV signals during exercise. Further, we performed real-time ANS analysis using HIF and confirmed that the exerciser's ANS variation experiences massive surges at points of acceleration and deceleration of the treadmill(similar to HRV).

• Journal of Platform Technology
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• v.9 no.1
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• pp.40-45
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• 2021

Our daily lives have changed a lot because of the COVID-19 pandemic. This is essential to reduce the spread of COVID-19 due to public health measures such as social distancing. At the same time, however, they are exposed to depression, anxiety disorders, depressive disorders, trauma and stress-related disorders. For this, we developed an application that can check HRV data and stress index by measuring ECG and PPG based on a Smart Watch device that can measure bio-signals in real time. In the case of the developed application, the heart rate is measured and displayed in real time to deliver basic exercise information by measuring exercise, steps and calories, and total distance, and smoothly based on blood pressure, heart rate, and HRV data as a measurement program. Through this, I believe that the IoT Smart Stress Care Application, which can manage mental health by itself, will be helpful to patients with stress and depressive trauma disorders.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.200-203
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• 2001

감성평가 실험시 피험자가 받는 작업부하의 영향을 실시간으로 평가하기 위하여 측정된 심전도 신호로부터 R-peak를 자동적으로 검출하여 심전도 관련 파리미터를 분석하는 시스템을 개발하였다. 이 시스템은 심전도 증폭기, A/D변환기, PC로 구성되었으며 National Instrument 사의 LabVIEW를 사용하여 소프트웨어를 개발하였다. 시스템 동작환경은 Microsoft사의 Window OS를 기반함으로서 시스템 이용자들에게 보다 친숙한 실험환경을 제시할 수 있다. 구현된 시스템은 실시간 HRV, Lorentz plot, LF/HF, HRV power spectrum의 3차원 선도를 디스플레이할 수 있다.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.3
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• pp.329-335
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• 2019

Annually, millions of children die from respiratory virus infections. Human rhinovirus (HRV) is a causative agent of severe respiratory infections in young, elderly, and asthmatic patients with weak immunity. In this study, 9,010 respiratory virus specimens were collected from January 2012 to December 2018 at Dankook University Hospital, Cheonan and examined by real-time reverse transcription polymerase chain reaction. Twelve respiratory viruses were detected. The mean detection rate was 21.3% (N=1,920/9,010), and the mean age of HRV-positive patients was 6.5 years (median age: 1.6 years, range: 0.0~96.0). The detection rate was the highest in July (32.4%) and the lowest in February (8.3%). When the detection rate was analyzed by age group, the detection rate was the second highest in patients aged 10~19 years. The co-infection rate of HRV was 35.3%, and the most common combination was with Adenovirus. Respiratory virus infections are known to occur in children and elderly people with weak immunity. However, in this study, the detection rate was second highest in patients aged 10~19 years. Indeed, the detection rate in this age group was more than 15%, except in January and February. These results suggested that steady-state studies on the infection patterns of HRV are required.

• Korean Journal of Microbiology
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• v.47 no.2
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• pp.117-123
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• 2011

The purpose of this study was to evaluate and compare different elution and concentration methods for optimization of human rotavirus (HRV) detection method using real-time RT-PCR and cell culture techniques. The leafy vegetable samples (lettuce, Chinese cabbage) were artificially inoculated with HRV. Viruses were extracted from the vegetables by two different elution buffers, buffer A (100 mM Tris-HCl, 50 mM glycine, 3% beef extract, pH 9.5) and buffer B (250 mM Threonine, 300 mM NaCl, pH 9.5), and the extracted viruses were concentrated by filtration and PEG precipitation sequentially. To determine infectivity of the viruses, the viruses recovered from the samples were infected to the MA-104 cells, and integrated cell culture real-time RT-PCR was performed at 1, 48, 72, 96, 120, 144, 168 h post-infection (p.i.). The elution buffer A was more efficient in extracting the virus from the produce samples tested than the buffer B, 29.54% and 18.32% of recoveries, respectively. The sensitivity of real-time RT-PCR method was markedly improved when the virus was concentrated by the filtration method. When the viruses were eluted and concentrated by buffer A and filtration, respectively, the average recovery rate was approximately 51.89%. When the viruses recovered from samples were infected to MA-104 cell, infectious HRV was detected within 48 h p.i. by ICC/real-time RT-PCR, whereas cytopathic effects were not observed until 72 h p.i. The optimized detection method evaluated in this study could be useful for rapid and reliable detection of HRV in fresh produce products and applied for detection of other food-borne viruses.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2157-2158
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• 2006

Heart Rate Variability (HRV) system is useful for evaluating the balance in homeostasis of autonomic nervous system. In this study, we implement HRV monitoring system by performing real time FFT spectrum analysis on R-R intervals data acquired from Electrocardiogram (ECG) acquisition and transmitting the data by RF communication module.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.543-543
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• 2000

A new method for HRV(heart rate variability) detection from the R-wave signal, based on the IPFM(integral pulse frequency modulation) model and its similarity to pulse position modulation, is presented. The proposed method exert lowpass filtering with a Kaiser window. In this paper, The proposed method presents a powerful, but simple, tool for investigation of HRV. It also guarantees real-time behavior. simplicity in design, and phase linearity. Even without the basic assumption of IPFM model. the new algorithm can still be used on-line and with higher performance. It is thoroughly proved that lowpass filtering is an ideal method for PSD(Power Spectrum Density) analysis of HRV.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.191-198
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• 2020

In this study, we proposed a real-time ECG analytical method for predicting stress and dangerous heart condition using the ECG signal in playing AR/VR device. A real-time diagnosis is used as R-R interval based HRV(:Heart rate variability), BPM(:Beats Per Minitue) and autonomic nervous research with through mapping method of two-dimensional planes. The ECG data were analyzed every 5 minutes and derived from autonomic nervous system diagnosis.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3233-3235
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• 2000

A new method for HRV(heart rate variability} detection from the R-wave signal, based on the IPFM (integral pulse frequency modulation) model and its similarity to pulse position modulation, is presented. The proposed method exert lowpass filtering with a Kaiser window. In this paper, The proposed method presents a powerful, but simple, tool for investigation of HRV. It also guarantees real-time behavior, simplicity in design, and phase linearity. Even without the basic assumption of IPFM model, the new algorithm can still be used on-line and with higher performance. It is thoroughly proved that lowpass filtering is an ideal method for PSD (Power Spectrum Density) analysis of HRV.

• Journal of the Ergonomics Society of Korea
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• v.18 no.3
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• pp.27-39
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• 1999

The purpose of this study was to approve the capability of human sensibility evaluation based on physiological responses and real-time subjective assessments. Three well-trained healthy human subjects were participated in the experiments. We measured physiological responses such as Heart Rate Variability(HRV), Galvanic Skin Response(GSR) and skin temperature under rest and visual stimulation conditions, respectively. Off-time subjective assessments were recorded before and after visual stimulations. Real-time subjective assessments were recorded during visual stimulations. The results of physiological responses and off-time and real-time subjective assessments were quantified and compared. The results showed that the correlation between physiological responses and real-time subjective assessments was high (83%) for both the positive and negative visual stimulation. The correlation between the physiological responses and off-time subjective assessments was high (83%) for the negative visual stimulation but was low (15%) for the positive visual stimulation. Although the current observation is preliminary and requires more careful experimental study, it appears that the correlation between real-time subjective assessment and physiological responses is higher than that of the off-time subjective assessment and physiological responses.