• Title/Summary/Keyword: HRV 분석

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A Study of GSR Signal Processing for Viral Reality System for Treatment of Mental Illness (가상현실 정신질환 치료시스템을 위한 GSR 신호분석에 관한 연구)

  • Ryu, Jong-Hyun;Beack, Seung-Hwa;Paek, Seung-Eun;Kim, Dong-Wan
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2693-2695
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    • 2004
  • Recently A virtual environment provides patient with stimuli which arouses phobia, and exposing to that environment makes him having ability to over come the fear. ECG and HRV are used in most virtual reality system. GSR is electrical impedance of biological tissues and the changes in impedance accompanying physiological activity. GSR is better than ECG or HRV for explaining mental states in other study. In this study, we will analysis GSR signal when a acrophobia patient and a normal is on high floor.

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Measurement of Human Sensibility by Bio-Signal Analysis (생체신호 분석을 통한 인간감성의 측정)

  • Park, Joon-Young;Park, Jahng-Hyon;Park, Ji-Hyoung;Park, Dong-Soo
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.935-939
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    • 2003
  • The emotion recognition is one of the most significant interface technologies which make the high level of human-machine communication possible. The central nervous system stimulated by emotional stimuli affects the autonomous nervous system like a heart, blood vessel, endocrine organs, and so on. Therefore bio-signals like HRV, ECG and EEG can reflect one' emotional state. This study investigates the correlation between emotional states and bio-signals to realize the emotion recognition. This study also covers classification of human emotional states, selection of the effective bio-signal and signal processing. The experimental results presented in this paper show possibility of the emotion recognition.

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Human Sensibility Measurement for Visual Picture Stimulus using Heart Rate Variability Analysis (심박변화 분석을 이용한 장면시자극에 대한 감성측정에 관한 연구)

  • 권의철;김동윤;김동선;임영훈;손진훈
    • Science of Emotion and Sensibility
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    • v.1 no.1
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    • pp.93-103
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    • 1998
  • In this paper, we present change of human sensiblity when the 26 healthy female subjects were exposed with visual picture stimulus. We used Intermational Affective Picture System as the visual stimulus. The methods are AutoRegressive(AR) spectrum which is a linear method and Return Map which is a nonlinear mithod. SR spectrum may variability(HRV). The LF/HF of HRV and the variation of Return Map were analyzed from ECG signal of the female subjects. Return Map of RR intervals were analyzed by computiong the variation. When the subjets were stimulated by the pleasant pictures, LF/HF and variation were decreased compared with unpleasant stimulus, We may obtain good parameters for the measurement of the change of human sensibility for the visual picture stimulus.

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An Analysis of Mixed Pixel in the Remote Sensing Image Data (위성탐사 이미지에서 혼합화소의 해석에 관한 연구)

  • Kim, Jin-Il;Park, Min-Ho;Kim, Sung-Chun
    • Journal of Korean Society for Geospatial Information Science
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    • v.3 no.2 s.6
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    • pp.91-100
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    • 1995
  • The aim of this study is to classify mixed information in a pixel of a remote sensing image data (in the case of SPOT HRV's band $1{\sim}3,\;20m{\times}20m$). First, the loss of information and the uncertainty of mixed pixel are examined. To solve the problems, methods by fuzzy sigmoid function and back-propagation neural network are suggested. Then. the study simulates and comparatively analyzes the two methods.

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A Study on the Extraction of Biosignal Paramters for the Computational Stress (연산 스트레스에 대한 감성 측정을 위한 생리 파라메터 추출에 대한 연구)

  • 하은호;김동윤;박광훈;임영훈;고한우;김동선;김승태
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 1999.11a
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    • pp.139-144
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    • 1999
  • 본 논문에서는 45명의 남자 대학생들에게 연산을 수행하게 한 후, 연산스트레스를 측정하기 위한 생리 파라메터의 추출에 대하여 연구하였다. 파라메터를 추출하기 위해서 1) 정규분포화를 위한 변환 2) 상관관계를 통해 상호관련성이 높은 파라메터를 조사 3) 휴식기간과 연산작업간의 파라메터의 값 비교를 통한 파라메터 표준화 4) 각 파라메터에 대해서 반복측정자료의 분산분석법을 통하여 검정함으로써 통계적으로 유의적인 차이가 있는 파라메터를 선정하였다. 위와 같은 절차를 통하여 연산스트레스의 지수화에 필요한 생리 파라메터로 Heart Rate, HRV의 LF/HF, HRV의 MF/(LF+HF), Return Map의 분산, Mean Temperature, GSR-Mean과 호흡수가 최종적으로 선정되었다.

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Associations Between Heart Rate Variability and Symptom Severity in Patients With Somatic Symptom Disorder (신체 증상 장애 환자의 심박변이도와 증상 심각도의 연관성)

  • Eunhwan Kim;Hesun Kim;Jinsil Ham;Joonbeom Kim;Jooyoung Oh
    • 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.

Characteristics in HRV(heart rate variability), GSR(galvanic skin response) and skin temperature for stress estimate (스트레스 평가를 위한 심박 변이도, 전기피부반응 및 피부온도 특성)

  • Cho, Young Chang;Kim, Min Soo
    • Journal of Korea Society of Industrial Information Systems
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    • v.20 no.3
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    • pp.11-18
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    • 2015
  • Stress is one of the major causes threatening the mental and physical health of human today. In this paper, we analyzed the heart rate variability(HRV), galvanic skin response(GSR), and skin temperature data measured from the university subjects before and after the class to examine the influence on bio-signal in stress environment. Thirty subjects from university students (aged between 21 and 27 years; mean=22.31, STD=1.45) took part in this study. From the experiment results, RMSSD(p=0.033), LF peak(p=0.003), VLF(p=0.045) were statistically significant from those of the control group(p<0.05) of HRV both in time and frequency domain. We observed that mean skin conductivity after the class(mean=5.993(uS), SD=3.406) is higher than that before the class(mean=3.039(uS), SD=2.628) by 97.2% on average and the skin temperature after the class($34.835{\pm}0.305$) is slightly higher than that before the class($34.471{\pm}0.281$) by 1.055% on average. The results in this research could be used to examine the autonomic response in clinical stress related research.

Convergence Implementing Emotion Prediction Neural Network Based on Heart Rate Variability (HRV) (심박변이도를 이용한 인공신경망 기반 감정예측 모형에 관한 융복합 연구)

  • Park, Sung Soo;Lee, Kun Chang
    • Journal of the Korea Convergence Society
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    • v.9 no.5
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    • pp.33-41
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    • 2018
  • The purpose of this study is to develop more accurate and robust emotion prediction neural network (EPNN) model by combining heart rate variability (HRV) and neural network. For the sake of improving the prediction performance more reliably, the proposed EPNN model is based on various types of activation functions like hyperbolic tangent, linear, and Gaussian functions, all of which are embedded in hidden nodes to improve its performance. In order to verify the validity of the proposed EPNN model, a number of HRV metrics were calculated from 20 valid and qualified participants whose emotions were induced by using money game. To add more rigor to the experiment, the participants' valence and arousal were checked and used as output node of the EPNN. The experiment results reveal that the F-Measure for Valence and Arousal is 80% and 95%, respectively, proving that the EPNN yields very robust and well-balanced performance. The EPNN performance was compared with competing models like neural network, logistic regression, support vector machine, and random forest. The EPNN was more accurate and reliable than those of the competing models. The results of this study can be effectively applied to many types of wearable computing devices when ubiquitous digital health environment becomes feasible and permeating into our everyday lives.

The Relationship between Physically Disability Persons Participation in Exercise, Heart Rate Variance, and Facial Expression Recognition (지체장애인의 운동참여와 심박변이도(HRV), 표정정서인식력과의 관계)

  • Kim, Dong hwan;Baek, Jae keun
    • 재활복지
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    • v.20 no.3
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    • pp.105-124
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    • 2016
  • The This study aims to verify the causal relationship among physically disability persons participation in exercise, heart rate variance, and facial expression recognition. To achieve such research goal, this study targeted 139 physically disability persons and as for sampling, purposive sampling method was applied. After visiting a sporting stadium and club facilities that sporting events were held and explaining the purpose of the research in detail, only with those who agreed to participate in the research, their heart rate variance and facial emotion awareness were measured. With the results of measurement, mean value, standard deviation, correlation analysis, and structural equating model were analyzed, and the results are as follows. The quantity of exercise positively affected sympathetic activity and parasympathetic activity of autonomic nervous system. Exercise history of physically disability persons was found to have a positive influence on LF/HF, and it had a negative influence on parasympathetic activity. Sympathetic activity of physically disability persons turned out to have a positive effect on the recognition of the emotion, happiness, while the quantity of exercise had a negative influence on the recognition of the emotion, sadness. These findings were discussed and how those mechanisms that are relevant to the autonomic nervous system, facial expression recognition of physical disability persons.