• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.118-123
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• 2011

Heart related diseases mainly caused by heavy work load and increasing stress in human daily life. Therefore, researches on mobile healthcare monitoring for daily life has been carried out. Notably, wearable healthcare monitoring system which has least restriction has been tried to provide an emergency alert of abnormal heart rate. In this study, we developed chair type unconstrained BCG measurement system which able to perform continuous heart status monitoring at the office and daily life in the unconstrained way. Furthermore, adaptive threshold is used to detect the heart rate from BCG signals. The HRV(heart rate variability) is calculated from heart rate interval. ECG signal measured using conventional method and BCG signal measured using unconstraint system are carried out simultaneously for the purpose of performance evaluation. From the comparison result, BCG signal shows a similar heart beat characteristic as ECG signal. This proves the possibility of practical implementation of unconstraint healthcare monitoring system. In addition, medical examination like valsalva maneuver is performed to observe the changes in HRV due to stress. By performing valsalva maneuver, heart is said to be placed under an artificial physical stress condition. Under this artificial physical stress condition, the time and frequency domain of HRV parameters are evaluated.

• International Journal of Vascular Biomedical Engineering
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• v.3 no.2
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• pp.17-24
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• 2005

The main purpose of our study is to propose a new methodology to develop the multi-parametric measure including linear and nonlinear measures of heart rate variability diagnosing cardiovascular disease. We recorded electrocardiogram for three recumbent postures; the supine, left lateral, and right lateral postures. Twenty control subjects (age: $56.70{\pm}9.23$ years), 51 patients with angina pectoris (age: $59.98{\pm}8.41$ years) and 13 patients with acute coronary syndrome (age: $59.08{\pm}9.86$ years) participated in this study. To develop the multi-parametric measure of HRV, we used the multiple discriminant analysis method among statistical techniques. As a result, the multiple discriminant analysis gave 75.0% of goodness of fit. When the linear and nonlinear measures of HRV are individually used as a clinical tool to diagnose cardiac autonomic function, there is quite a possibility that the wrong results will be obtained due to each measure has different characteristics. Although our study is a preliminary one, we suggest that the multi-parametric measure, which takes into consideration the whole possible linear and nonlinear measures of HRV, may be helpful to diagnose the cardiovascular disease as a diagnostic supplementary tool.

• International Journal of Vascular Biomedical Engineering
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• v.3 no.1
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• pp.14-22
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• 2005

In the present study, our aim is to investigate whether responses to the head-up tilt (HUT) on nonlinear properties of heart rate variability (HRV) in young and elderly subjects are different or not. Thirteen young-healthy subjects ($24.5{\pm}3.7$ years) and 18 old-aged healthy subjects ($74.5{\pm}7.4$ years) participated in this study. An electrocardiogram (ECG) in the supine posture, at $0^{\circ}$, and in the standing posture, at $70^{\circ}$ of head-up tilt, was recorded. Detrended fluctuation analysis (DFA) and approximate entropy (ApEn), measures of short-/long-term correlation properties and overall complexity of heart rate (HR) respectively, along with spectral components of HR variability (HRV) were analyzed for both the supine and HUT postures. We observed that the short-term fractal exponent ${\alpha}_1$ increased during HUT posture (F(1, 29) = 39.79, P = 0.000), especially, the young subjects showed a significantly higher values compared to the elderly subjects. ApEn significantly decreased (F(1, 29) = 8.61, P = 0.006) during HUT posture. HUT posture decreased the complexity in HR dynamics and increased short-term fractal exponent values in young subjects but not in elderly subjects. These results imply that there are differences of response to HUT on nonlinear properties between young and elderly subjects.

• 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).

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.275-278
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• 1997

Standard methods estimating the power spectral density(PSD) from an irregularly sampled cardiac event series require deriving a new evenly-spaced signal applicable to those methods. To avoid that requirement, in this study, the power spectrum of heart rate variability was estimated by Lomb-Scargle's algorithm, which is a means of obtaining PSD estimates directly from irregularly sampled timeseries observed in astronomy. To assess the performance of Lomb-Scargle algorithm in the power spectral analysis of heart rate variability, it was applied to various cardiac event series derived through integral pulse frequency modulation model(IPFM) simulation and from real ECG signals, and the resultant power spectra was compared with those obtained by a conventional method based on the FFT. In result, it is concluded that Lomb-Scargle's periodogram is very effective in the power spectral analysis of heart rate variability, especially in the presence of arrhythmia and/or dropouts of cardiac events.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1370-1378
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• 2018

There is a problem to measure neutral bio-signals during sleep because of inconvenience of attaching lots of sensors. In this study, we measured single electrocardiogram(ECG) signal and analyzed the correlation with sleep. After R-peak detection from ECG signal, we extracted 9 features from time and frequency domain of heart rate variability(HRV). Mean of HRV, RR intervals differing more than 50ms(NN50), and divided by the total number of all RR intervals(pNN50) have significant differences in each sleep stage. Specially, the mean HRV has an average of 87.8% accuracy in classifying sleep and awake status. In the future, the measurement ECG signal minimizes inconvenience of attaching sensors during sleep. Also, it can be substituted for the standard sleep measurement method.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.2
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• pp.103-117
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• 2010

In this study, the heart rate variability(HRV) signal of operating patient was acquired according to anesthesia progress and identified to evaluation possibility of depth of anesthesia in each anesthesia stage. The HRV signal was analyzed time-frequency domain applied to Wigner-Ville distribution method, the characteristic parameters were extracted for evaluation of depth of anesthesia in each anesthesia stage. The progress of general anesthesia was divided into the states of pre-operation, induction of anesthesia, operation, awaking and post-operation.

• Journal of Biomedical Engineering Research
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• v.12 no.3
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• pp.209-214
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• 1991

Digital fetal monitoring system based on the personal computer combined with the digital signal processing (DSP) board was implemented. The DSP board acquires and digitally processes ultra- sound fetal Doppler signal for digital signal conditioning, rectification, low -pass filtering, autocorrealtion function calculation and its peak detection. The personal computer interfaced with the DSP board is in charge of graphic display, hardcopy, data transmission and on -line analysis of fetal heart rate change including on - line warning system, base -line estmation, acceleration, deceleration and variability. It is one of the most suitable situation to apply the DSP chip for siganl conditioning, digital filtering of ultrasound fetal Dopier signal and fetal heart rate estimation using autocorrelation technique .

• Journal of Society of Preventive Korean Medicine
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• v.14 no.2
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• pp.105-120
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• 2010

Objectives : This study aims to evaluate the effects of expiration-to-inspiration time ratio (E/I-ratio) on heart rate, which represents cardiac autonomic function, and cold-heat in the healthy people. Methods : 49 healthy young volunteers(male : female = 32 : 17) were recruited in the study. The participants completed the questionnaire for yin-yang pattern identification and then we measured the chest plethysmogram for respiration signal and the electrocardiogram for NN intervals during different E/I-ratio from 1 to 2. We compared heart rate variability including RMS-SD, VLF, LF and HF, and the trend-cycle factors decomposed from NN interval data by time series analysis among the respective E/I-ratio. We also confirmed the difference on the trend-cycle factors according to the score of the questionnaire for cold and heat pattern identification. Results : There were differences on the trend-cycle factors from NN interval data, but no significant difference on heart rate variability, among the respective E/I-ratio. We also found significant relationship between the trend-cycle factors and the heat pattern identification scores. Conclusions : The results indicate that cardiac autonomic function can be modulated by the E/I-ratio and the modulation will be slower and more tendencious than respiratory sinus arrhythmia.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.15-22
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• 2000

The analysis of power spectrum based on linear AR model is applied widely to quantize the response of autonomic nerve noninvasively, In this paper, we estimate the power spectrum density for heartrate variability of the electrocadiogram and pulse wave for short term data(less than two minute), The time series of heart rate variability is obtained from the time interval(RRI, PPI) between the feature point of the electrocadiogram and pulse wave for normal person, The generated time series reconstructed into new time series through polynomial interpolation to apply to the AR mode. The power spectrum density for AR model is calculated by Burg algorithm, After applying AR model, the power spectrum density for heart rate variability of the electrocadiogram and the pulse wave is shown smooth spectrum power at the region of low frequence and high frequence, and that the power spectrum density of electrocadiogram and pulse wave has similar form for same subject.