• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1906-1908
• /
• 2007

This study describes a software engine that can evaluate human sensibility using a heart rate variable(HRV) of hypochodriac or old people, and suggest biofeedback to enhance their emotion. To develop the software engine, using PPG signal heart rate and HRV are calculated. Using the FFT spectra of HRV, human sensibility is estimated. And a biofeedback software is designed with motion image player, breathing control and other function modules.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.6
• /
• pp.701-706
• /
• 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 Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.6
• /
• pp.865-871
• /
• 2012

In this study, ambulatory electrocardiogram(ECG) signal and the rhythms of heart beats are visualized in terms of R-R intervals and Heart Rate Variability(HRV) in the environment of an android plaform. With this aim, Graphical User Interface(GUI) is implemented by executing multi-thread Java programming modules including ECG, heart-beats, tachogram and visualization unit. ECG signals are acquired in an android device by receiving the data from ambulatory ECG sensory system. Finite Impulse Response(FIR) filters are implemented to eliminate the baseline wandering noises contained in the ambulatory signals and DC-offset level in R-R interval data. With simulating the normal or stress emotional state of a subject, we can find the fact that HRV can be successfully estimated and visualized in an android smart phone platform.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.05
• /
• pp.275-278
• /
• 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 Biomedical Engineering Research
• /
• v.24 no.1
• /
• pp.1-8
• /
• 2003

The job of long distance driving is likely to be fatiguing and requires long period alertness and attention, which make considerable demands of the driver. Driving fatigue contributes to driver related with accidents and fatalities. In this study, we investigated the relationship between the number of hours of driving and driving fatigue using heart rate variability(HRV) signal. With a more traditional measure of overall variability (standard deviation, mean, spectral values of heart rate). Nonlinear characteristics of HRV signal were analyzed using Approximate Entropy (ApEn) and Poincare plot. Five subjects drive the four passenger vehicle twice. All experiment number was 40. The test route was about 300Km continuous long highway circuit and driving time was about 3 hours. During the driving, measures of electrocardiogram(ECG) were performed at intervals of 30min. HRV signal, derived from the ECG, was analyzed using time, frequency domain parameters and nonlinear characteristic. The significance of differences on the response to driving fatigue was determined by Student's t-test. Differences were considered significant when a p value < 0.05 was observed. In the results, mean heart rate(HRmean) decreased consistently with driving time, standard deviation of RR intervals(SDRR), standard deviation of the successive difference of the RR intervals(SDSD) increased until 90min. Hereafter, they were almost unchanging until the end of the test. Normalized low frequency component $(LF_{norm})$, ratio of low to high frequency component (LF/HF) increased. We used the Approximate Entropy(ApEn), Poincare plot method to describe the nonlinear characteristics of HRV signal. Nonlinear characteristics of HRV signals decreased with driving time. Statistical significant is appeared after 60 min in all parameters.

• International Journal of Vascular Biomedical Engineering
• /
• v.3 no.2
• /
• pp.10-16
• /
• 2005

Because patients with coronary artery disease (CAD) have depressed vagal modulation and the mortality risk from acute myocardial infarction is lower in patients with higher vagal modulation, methods that can increase vagal modulation are desirable in patients with CAD. We intended to inspect the effect of recumbent posture on vagal modulation. By using angiography, 33 patients with abnormal (CAD group) and 33 patients with normal coronary arteries (control group) were studied. The nonlinear as well as the linear characteristics of heart rate variability (HRV) were analyzed on these patients in three recumbent postures: namely, the supine, right lateral decubitus, and left lateral decubitus postures. The lower the normalized high-frequency power (nHF) in the supine or left lateral decubitus posture, the higher the increase in the nHF when the posture was changed from supine or left lateral decubitus to right lateral decubitus in both groups of patients. Right lateral decubitus posture can lead to the highest vagal modulation and the lowest sympathetic modulation among the three recumbent postures in both normal and patients with CAD. Therefore, the right lateral decubitus posture can be used as an effective physiologic vagal enhancer in patients with CAD.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.9
• /
• pp.328-334
• /
• 2012

Continuous fetal heart beat monitoring has assisted clinicians in assuring fetal well-being during antepartum and intrapartum. Fetal heart rate (FHR) is an important parameter of fetal health during pregnancy. The Doppler ultrasound is one of very useful methods that can non-invasively measure FHR. Although it has been commonly used in clinic, inaccurate heart rate reading has not been completely resolved.. The objective of this study is to improve detection algorithm of FHR from Doppler ultrasound signal with simple method. We modified autocorrelation function to enhance signal periodicity and adopted adaptive window size and shifted for data segment to be analysed. The proposed method was applied to real measured data, and it was verified that beat-to-beat FHR estimation result was comparable with the reference fetal ECG data. This simple and effective method is expected to be implemented in the embedded system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.8
• /
• pp.2008-2016
• /
• 2014

With the increased attention about health care and management of heart diseases, ubiquitous healthcare services and related devices have been actively developed recently. In this paper we developed a mobile healthcare system which consists of smartphone and patch-type ECG measuring device. This system is capable of monitoring, storing, and sending bio signals such as ECG, heart rate, heart rate variability as well as exercise management functions through heart rate zones. With monitoring bio signal continuously by mobile healthcare system and wearable device like us, people can prevent chronic disease and maintain good health. Here we report our implementation results on real platforms.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.05
• /
• pp.165-170
• /
• 1997

In this paper, we consider the aortic sinus baroreceptor, which is the most representative baroreceptors sensing the variance of pressure in the cardiovascular system(CVS), and propose heart activity control model to observe the effect of delay time in heart period and stroke volume under the regulation of baroreflex in arotic sinus. The proposed heart activity baroreflex regulation model contains CVS electric circuit sub-model, baroreflex regulation sub-model and time delay sub-model. In these models, applied electric circuit sub-model is researched by B.C.Choi and the baroreflex regulation sub-model transforms the input, the arotic pressure of CVS electric circuit sub-model, to outputs, heart period and stroke volume by mathematical nonlinear feedback. We constituted the time delay sub-model to observe sensitivity of heart activity baroreflex regulation model by using the variable value to represent the control signal transmission time from the output of baroreflex regulation model to efferent nerve through central nervous system. The simulation object of this model is to observe variability of the CVS by variable value in time delay sub-model. As simulation results, we observe three patterns of CVS variability by the time delay. First, if the time delay is over 2.5 sec, arotic pressure, stroke volume and heart rate is observed nonperiodically and irregularly. Second, if the time delay is from between 0.1 sec and 0.25 sec, the regular oscillation is observed. Finally, if time delay is under 0.1 sec, then heart rate and arotic pressure-heart rate trajectory is maintained in stable state.

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