• The Korean Journal of Physiology and Pharmacology
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• v.28 no.3
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• pp.253-264
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• 2024

Chronic neuropathic pain (CNP) is a complex condition often arising from neural maladaptation after nerve injury. Understanding CNP complications involves the intricate interplay between brain-heart dynamics, assessed through quantitative electroencephalogram (qEEG) and heart rate variability (HRV). However, insights into their interaction in chronic pain are limited. Resting EEG and simultaneous electrocardiogram (lead II) of the participants were recorded for qEEG and HRV analysis. Correlations between HRV and qEEG parameters were calculated and compared with age, sex, and body mass index (BMI)-matched controls. CNP patients showed reduced HRV and significant increases in qEEG power spectral densities within delta, theta, and beta frequency ranges. A positive correlation was found between low frequency/high frequency (LF/HF) ratio in HRV analysis and theta, alpha, and beta frequency bands in qEEG among CNP patients. However, no significant correlation was observed between parasympathetic indices and theta, beta bands in qEEG within CNP group, unlike age, sex, and BMI-matched healthy controls. CNP patients display significant HRV reductions and distinctive qEEG patterns. While healthy controls exhibit significant correlations between parasympathetic HRV parameters and qEEG spectral densities, these relationships are diminished or absent in CNP individuals. LF/HF ratio, reflecting sympathovagal balance, correlates significantly with qEEG frequency bands (theta, alpha, beta), illuminating autonomic dysregulation in CNP. These findings emphasize the intricate brain-heart interplay in chronic pain, warranting further exploration.

• Korean Journal of Biological Psychiatry
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• v.15 no.3
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• pp.186-193
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• 2008

Objectives : The authors tried to investigate the characteristics of Heart Rate Variability(HRV) among the subjects with metabolic syndrome for testing the possibility of clinical application of HRV in evaluating metabolic syndrome. Methods : We examined the difference of the means of HRV between 122 subjects of metabolic syndrome and 1057 healthy controls using T-test, and the change of means in HRV according to increasing risk factors of metabolic syndrome. Using multiple regression analysis, we examined the association of HRV with the risk factors of metabolic syndrome. Results : The HRV indices including SDNN(Standard Deviation of all normal NN intervals), RMSSD(the square Root of the Mean Squared Differences of successive all normal NN interval), TP(Total Power), LF(Low Freuency), and HF(High Frequency) were significantly lower in the metabolic syndrome group than in the normal control group, and the means of all HRV indices except LF/HF were decreased consistently according to increasing risk factors of metabolic syndrome. The fasting glucose, triglyceride, and waist circumference were dependent factors that contributed significantly to the change of HRV. Conclusion : These findings suggest metabolic syndrome adversely affects cardiac autonomic system and HRV could be a useful method for evaluating metabolic syndrome.

• Progress in Medical Physics
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• v.10 no.3
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• pp.141-149
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• 1999

This research analyzed the HRV signals by using wavelet transform to observe the activities of autonomous nervous system in a sleep state. This research also restructured the HRV signals from electrocardiogram and by using coefficient which was obtained through wavelet transform, analyzed the signals by frequency bandwidth. Then compared the analyzed results with existing frequency analyzing method using AR model techniques. The suggested wavelet coefficient from power spectrum component in the study shows a similar tendency with the results from FFT or AR model technique. Therefore, it can be found that power spectrum analyzing method by wavelet coefficient is a useful as a tool for analyzing autonomous nervous system activities using HRV signals. Since the suggested method able to clearly depict the progression of change in time zone, which was once impossible with the existing methods, it is presumed that it will be useful in other physiological signals.

• Journal of Korean Biological Nursing Science
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• v.21 no.3
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• pp.178-187
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• 2019

Purpose: The purpose of this study was to investigate how college students' perceived stress, cognitive stress, and somatization affect their heart rate variability (HRV). Methods: This study is a cross-sectional survey research on 191 university students, registered at the G University. The perceived stress scale (PSS) and cognitive stress response scale, were used to assess level of stress. The somatization symptom scale of the Symptom Check List 90 (SCL-90), was used to assess level of somatization caused by stress. To assess heart rate variability (HRV), we conducted a five-minute test using a pulse wave analyzer, to analyze short-term HRV. Results: The SCL-90 somatization score had relatively high positive correlation (p< .001) with cognitive stress, but low positive correlation (p< .001) with perceived stress. Cognitive stress response had low negative correlation (p< .001) with 1nSDNN and 1nRMSSD among HRV parameters. Perceived stress was not correlated with HRV. Multiple regression analysis showed that variables of perceived stress, cognitive stress, and somatization symptoms, could not explain HRV. By contrast, one of the HRV indicators, 1nSDNN, was affected by age, gender, and aggressive-hostile thought, the latter being a subscale of the cognitive stress response scale. Conclusion: This study suggests that stress evaluation for people in early adulthood will be more effective, if the evaluation examines cognitive stress and heart rate variability.

• Biomedical Science Letters
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• v.19 no.1
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• pp.55-60
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• 2013

This study was to know the effects of massage on the back region in order to reduce stress in middle age women. To investigate the effects of massage to the stress levels of middle aged women, we evaluated blood pressure (BP), heart rate variability (HRV), and ultrasonography before and after back massage. The blood pressure after massage was reduced when compared to that of pre-massage. The HRV spectrum analysis was used Frequency domain analysis such as Mean HRV, normalized low frequency (norm LF), norm high frequency (norm HF), and LF/HF ratio. Post-massage BP tended to be low, but not statistical significant. After Massage, the Mean HRV, norm LF, and LF/HF ratio were significantly reduced, while norm HF was significantly increased as compared with pre-massage. The muscle layer and fat layer were significantly diminished by massage. The study was suggested that massage may be an effective treatment for relief of stress.

• Science of Emotion and Sensibility
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• v.2 no.2
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• pp.31-36
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• 1999

본 연구의 목적은 후각 자극에 의한 감성의 변화를 주관적 검사와 동시에 시행한 심전도에서 추출한 HRV parameter와의 상관관계를 보고자 함이다. 후각 자극은 0.6% orange와 2.5% valeric acid를 일정 flow와 일정 농도를 코 점막에 건조를 방지하기 위해 수증기로 포화시킨 향자극기로 주었다. 향의 주관적 검사에서 오렌지향은 친숙하고 쾌하다고 하였으며, valeric acid의 경우 불쾌하고 성가시고 친숙하지 않는 감성을 표시하였다. 이러한 쾌하고 불쾌한 향자극에 대한 HRV 분의 활동이 우세하였음을 확인하였다. 결론적으로 HRV 스펙트럼 분석이 감성의 변화를 객관적인 지표로 나타내는데 유용한 정보로서의 가능성을 제시히고자 하였다.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.216-222
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• 2013

It is known that blood circulation in human body causes the skin tone to change concurrently with heartbeats. A number of apps have been developed to measure the heartbeat using smartphone camera; however, no any further analysis is performed. In this paper we propose an algorithm that detects heartbeats from the phone's camera and further extracts the heart rate variability (HRV). We compare the HRV extracted from the camera with the HRV extracted from the electrocardiogram. We estimated a number of commonly used HRV characteristics and compared them. Our results show that smartphone camera leads to slightly overestimated characteristics although the difference in extracted HRV signals is negligible. As a consequence we suggest that a smartphone camera can be employed in a quick heart diagnosis and diagnosis of autonomic nervous system.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.10 no.2
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• pp.104-120
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• 2006

Background : Pulse-respiration ratio has been used for estimating subject's status in oriental medicine. Pulse and respiration is strongly associated with autonomic nerve system. But there is no research about correlation between pulse-respiration ratio and autonomic nerve system. Objectives : We performed this study to know correlation between pulse-respiration ratio and HRV(heart rate variability) that shows autonomic nerve system status well and to clarify clinical meaning of pulse-respiration ratio. Methods : After subject's 10 minutes rest, we measured subject's ECG, respiration pattern and HRV. In this research, subject's number is 95(Male 50/Female 45). We calculated pulse-respiration ratio from ECG and respiration pattern. Then, we analyzed correlation between pulse-respiration ratio and HRV parameters in all subjects, 2 group divided by Wan-Maek(P-R ratio 4.28). We tried to compare HRV parameters among Wan-Maek, Sak-Maek and Ji-Maek group. Correlation analysis between pulse-respiration Ratio and Pulse rate, respiration rate is performed. Finally correlation analysis between Respiration and HRV parameters in all subjects, 2 group divided by Wan-Maek(4.28) is studied. Results : 1. Mean pulse-respiration is 4.10${\pm}$0.67, Mean pulse rate is 68.06${\pm}$7.82bpm, Mean respiration rate is 16.81${\pm}$2.72 times per minute in all subjects. 2. Correlation analysis between pulse-respiration ratio and HRV parameters of high pulse-respiration ratio group is not significant. But, in low pulse-respiration ratio group, HFnorm(correlation coefficient 0.306, p= 0.018), lnHF (0.308, p=0.002) is significantly correlated with pulse-respiration ratio. 3. Comparison of HRV parameters among Wan-Maek, Sak-Maek and Ji-Maek Group is not significant. 4. Pulse-respiration ratio is more affected by respiration rate(correlation coefficient-0.17, p=0.000) than pulse rate (correlation coefficient 0.396, p=0.000). 5. Correlation analysis between respiration rate and HRV parameters of high pulse-respiration ratio group is not significant. But, in low pulse-respiration ratio group, HFnorm (correlation coefficient -0.327, p=0.011), LF/HF(0.346, p=0.007), lnHF (-0.355, p=0.006) are significantly correlated with respiration rate. Conclusion : Pulse-respiration ratio and parasympathetic index has positive correlation. The closer Wan-Maek, The higher parasympathetic index in low pulse-respiration ratio group. Respiration rate is more related with pulse-respiration ratio than pulse rate. Respiration is negatively correlated with autonomic parameters. And the slower respiration, the higher parasympathetic index in low pulse-respiration ratio group.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1395-1405
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• 2017

In this paper, we analyses heart beat data to identify subjects stress state (binary) using heart rate variability (HRV) features extracted from heart beat data of the subjects and implement supervised machine learning techniques to create the mental stress classifier. There are four steps need to be done: data acquisition, data processing (HRV analysis), features selection, and machine learning, before doing performance measurement. There are 56 features generated from the HRV Analysis module with several of them are selected (using own algorithm) after computing the Pearson Correlation Matrix (p-values). The results of the list of selected features compared with all features data are compared by its model error after training using several machine learning techniques: support vector machine, decision tree, and discriminant analysis. SVM model and decision tree model with using selected features shows close results compared to using all recording by only 1% difference. Meanwhile, the discriminant analysis differs about 5%. All the machine learning method used in this works have 90% maximum average accuracy.

• KIEAE Journal
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• v.16 no.6
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• pp.123-128
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• 2016

Purpose: In order to save the energy consumption of buildings, buildings have been constructed with high performance insulation or airtightness. However, high performance insulation or air tightness has led to a poor indoor air quality. Therefore, HRV(Heat Recovery Ventilator) has received attention to save the energy consumption and insure a good air quality. Because existing research is almost about the performance of HRV in residential buildings, This study analyzed the effect of HRV on cooling energy consumption in commercial office building. Method: This study was proceeded at commercial office building in In-cheon. In order to evaluate the energy consumption of HRV, this study proposed two methods: estimating energy consumption of the room installed AHU(Air Handling Unit) system; estimating energy consumption of the room installed HRV system. Therefore, comparison of two methods was proceeded to evaluate energy performance of each method. Result: As the result of comparison between rooms installed AHU and HRV, the experiment showed that energy consumption of the room installed HRV system is about 22% less than the room of AHU system. This conclusion is considered because the room installed HRV system have maintained temperature well at set point temperature $26^{\circ}C$.