• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.93-100
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• 1988

The Auto Regressive Parameter Estimation and Pattern Classification of EKG Signal for Automatic Diagnosis. This paper presents the results from pattern discriminant analysis of an AR (auto regressive) model parameter group, which represents the HRV (heart rate variability) that is being considered as time series data. HRV data was extracted using the correct R-point of the EKG wave that was A/D converted from the I/O port both by hardware and software functions. Data number (N) and optimal (P), which were used for analysis, were determined by using Burg's maximum entropy method and Akaike's Information Criteria test. The representative values were extracted from the distribution of the results. In turn, these values were used as the index for determining the range o( pattern discriminant analysis. By carrying out pattern discriminant analysis, the performance of clustering was checked, creating the text pattern, where the clustering was optimum. The analysis results showed first that the HRV data were considered sufficient to ensure the stationarity of the data; next, that the patern discrimimant analysis was able to discriminate even though the optimal order of each syndrome was dissimilar.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.183-190
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• 2015

Invasive blood pressure (IBP) is measured for the patient's real time arterial pressure (ABP) to monitor the critical abrupt disorders of the cardiovascular system. It can be used for the estimation of cardiac output and the opening and closing time detection of the aortic valve. Although the unexplained inflections on ABP make it difficult to find the mathematical relations with other cardiovascular parameters, the estimations based on ABP for other data have been accepted as useful methods as they had been verified with the statistical results among vast patient data. Previous windkessel models were composed with systemic resistance and vascular compliance and they were successful at explaining the average systolic and diastolic values of ABP simply. Although it is well-known that the blood pressure reflection from peripheral arteries causes complex inflection on ABP, previous models do not contain any elements of the reflections because of the complexity of peripheral arteries' shapes. In this study, to simulate a reflection wave of blood pressure, a new mathematical model was designed with four elements that were the impedance of aorta, the compliance of aortic arch, the peripheral resistance, and the compliance of peripheral arteries. The parameters of the new model were adjusted to have three types of arterial blood pressure waveform that were measured from a patient. It was used to find the relations between the inflections and other cardiovascular parameters such as the opening-closing time of aortic valve and the cardiac output. It showed that the blood pressure reflection can bring wide range errors to the closing time of aortic valve and cardiac output with the conventional estimation based on ABP and that the changes of one-stroke volumes can be easily detected with previous estimation while the changes of heart rate can bring some error caused by unexpected reflections.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.209-215
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• 2019

The most important personal health care in digital health care is a very important issue mainly for chronic diseases. Therefore, it is important to develop a simple wearable device for real-time health management. Existing blood pressure estimation wearable devices use PPG characteristics to analyze PTT and propose blood pressure estimation algorithms. However, the influencing factors of the algorithm such as the reproducibility of PPG, whether to apply various PTTs, and variables generated from the physical differences of the measurers are actually very complex. Therefore, in this study, the correlation between PTT, SBP, and DBP was analyzed, and it was designed to use PPG sensors for device miniaturization. The blood pressure estimation algorithm took into account differences in PPG, heart rate, and personal variables.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.62-74
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• 2020

Although the government and local governments devote efforts to activate bicycles, they only access to the supply infrastructure such as bike lanes and the public bicycle rental service centers without considering the measures to overcome the geographical constraints of slope. Therefore, this study constructs bicyclist's energy consumption estimation model through experimental methods of slope gradient and heart rate measurement and suggest the bicycle route choice model which could minimize the energy by the slope gradient. After calculating the RMSE of the estimated energy consumption by applying this model to the simulation section, it is confirmed to be 41% better than the model which does not reflect slope gradient. The results of this study are expected to be applied to the bicycle infrastructure planning that considers both longitude and transverse of bike lanes and the algorithm of bicycle route guidance system in the future.

• The Korean Journal of Pain
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• v.32 no.3
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• pp.168-177
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• 2019

Background: Brennan's rodent paw incision model has been extensively used for understanding mechanisms underlying postoperative pain in humans. However, alterations of physiological parameters like blood pressure and heart rate, or even feeding and drinking patterns after the incision have not been documented as yet. Moreover, though eicosanoids like prostaglandins and leukotrienes contribute to inflammation, tissue levels of these inflammatory mediators have never been studied. This work further investigates the antinociceptive effect of protein C after intra-wound administration. Methods: Separate groups of Sprague-Dawley rats were used for quantitation of cyclooxygenase (COX) activity and leukotriene B4 level by enzyme-linked immunosorbent assay, as well as estimation of cardiovascular parameters and feeding and drinking behavior after paw incision. In the next part, rats were subjected to incision and $10{\mu}g$ of protein C was locally administered by a micropipette. Both evoked and non-evoked pain parameters were then estimated. Results: COX, particularly COX-2 activity and leukotriene B4 levels increased after incision. Hemodynamic parameters were normal. Feeding and drinking were affected on days 1 and 3, and on day 1, respectively. Protein C attenuated non-evoked pain behavior alone up to day 2. Conclusions: Based upon current observations, Brennan's rodent paw incision model appears to exhibit a prolonged period of nociception similar to that after surgery, with minimal interference of physiological parameters. Protein C, which is likely converted to activated protein C in the wound, attenuated the guarding score, which probably represents pain at rest after surgery in humans.

• 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.

• Journal of the Ergonomics Society of Korea
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• v.18 no.1
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• pp.121-131
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• 1999

There have been many questionnaires, catecholeamins analysis and bio-signal analysis to analyze human stress condition through out the years, and especially researches in bio-signal analysis have been actively increasing. The purpose of our research is Quantitative analysis of stress with synthesis of bio-signals. The stress status was estimated using the bio-signals and fuzzy theory which combines these signals and physiological knowledge. Stress was estimated by a 'coin-stacking' experiment with two type-relax and stress status. To do the experiment EMG, respiration, periphery temperature, heart rate and skin conductances were used to evaluate human stress stages. The system was tested to 10 healthy persons and achieved a template of a stress progress and stress variations were classified to 4 steps by continuous or rising status of stress progress.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.107-116
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• 2021

This study aims to investigate the effect of multisensory stimulation on relieving the stress experienced by drivers. The photoplethysmograms (PPGs) of 30 healthy subjects were measured, and their subjective response to stressful situations and normal driving were evaluated. The subjects underwent nonstimulation and multisensory stimulation in stressful driving situations. Heart rate estimation from the PPG was collected via an ear-type sensor to reduce movement noise. The signals acquired were sampled at 200 Hz using BIOPAC PPG100C. Heart rate variability (HRV) was analyzed to compare the effect of multisensory stimulation on stress situations. In the multisensory stimulation, blue, green, and yellow were used for the visual sensory system; white, pink, and brown noises were used for the auditory sensory system; and lavender, lemon, and rosemary were used for the olfactory sensory system. No difference was observed in the subjective evaluation; however, the HRV results showed an increased HF (%) and decreased LF (%) and LF/HF (%) in the multisensory stimulation (e.g., green, pink noise, and rosemary) when compared to the nonstimulation.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.108-117
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• 2023

Objectives : Somatic symptom disorder (SSD) is characterized by the manifestation of a variety of physical symptoms, but little is known about differences in autonomic nervous system activity according to symptom severity, especially within patient groups. In this study, we examined differences in heart rate variability (HRV) across symptom severity in a group of SSD patients to analyze a representative marker of autonomic nervous system changes by symptoms severity. Methods : Medical records were retrospectively reviewed for patients who were diagnosed with SSD based on DSM-5 from September 18, 2020 to October 29, 2021. We applied inverse probability of treatment weighting (IPTW) methods to generate more homogeneous comparisons in HRV parameters by correcting for selection biases due to sociodemographic and clinical characteristic differences between groups. Results : There were statistically significant correlations between the somatic symptom severity and LF (nu), HF (nu), LF/HF, as well as SD1/SD2 and Alpha1/Alpha2. After IPTW estimation, the mild to moderate group was corrected to 27 (53.0%) and the severe group to 24 (47.0%), and homogeneity was achieved as the differences in demographic and clinical characteristics were not significant. The analysis of inverse probability weighted regression adjustment model showed that the severe group was associated with significantly lower RMSSD (β=-0.70, p=0.003) and pNN20 (β=-1.04, p=0.019) in the time domain and higher LF (nu) (β=0.29, p<0.001), lower HF (nu) (β=-0.29, p<0.001), higher LF/HF (β=1.41, p=0.001), and in the nonlinear domain, significant differences were tested for SampEn15 (β=-0.35, p=0.014), SD1/SD2 (β=-0.68, p<0.001), and Alpha1/Alpha2 (ß=0.43, p=0.001). Conclusions : These results suggest that differences in HRV parameters by SSD severity were showed in the time, frequency and nonlinear domains, specific parameters demonstrating significantly higher sympathetic nerve activity and reduced ability of the parasympathetic nervous system in SSD patients with severe symptoms.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.991-993
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• 1999

This study proposed a new algorithm to assess autonomic function activity using Time-Frequency Representation(TFR). TFR is a way of describing the time-valiant energy of a signal. A discrete Wigner representation that is capable of filtering out any cross terms occuring in the Wigner-Ville Distribution(WVD) is used for time-variant energy distribution of heart rate variability(HRV) signals. And the marginal condition are evaluated to estimate power spectrum of HRV signals. The proposed algorithm showed that estimated power spectrum of HRV signals well describe the autonomic nerve system function and also showed the dynamics of autonomic nervous system response.