The Determination of the Duration of ElectroconvulsiveTherapy-Induced Seizure Using Local Standard Deviationof the Electroencephalogram Signal and the Changesof the RR Interval of Electrocardiogram

Objectives@#ZZIn electroconvulsive therapy (ECT) research and practice, the precise determination of seizure duration is importantin the evaluation of clinical relevance of the ECT-induced seizure. In this study, we have developed computerized algorithms to assessthe duration of ECT-induced seizure. @*Methods@#ZZSubjects included 5 males and 6 females, with the mean age of 33.1 years. Total 55 ECT sessions were included in theanalysis. We analyzed the standard deviation of a finite block of electroencephalography (EEG) data and the change in the local slope ofRR intervals in electrocardiography (ECG) signals during ECT-induced seizure. And then, we compared the calculated seizure durationsfrom EEG recording (EEG algorithm) and ECG recording (ECG algorithm) with values determined by consensus of clinicians basedon the recorded EEG (EEG consensus), as a gold standard criterion, in order to testify the computational validity of our algorithms. @*Results@#ZZThe mean seizure durations calculated by each method were not significantly different in sessions with abrupt flattenedpostictal suppression and in sessions with non-abrupt flattened postictal suppression. The intraclass correlation coefficients (95% confidenceinterval) of the three methods (EEG algorithm, ECG algorithm, EEG consensus) were significant in the total sessions [0.79(0.70–0.86)], the abrupt flattened postictal suppression sessions [0.84 (0.74–0.91)], and the non-abrupt flattened postictal suppressionsessions [0.67 (0.45–0.84)]. Correlations between three methods were also statistically significant, regardless of abruptness of transition. @*Conclusions@#ZZOur proposed algorithms could reliably measure the duration of ECT-induced seizure, even in sessions with nonabrupttransitions to flat postictal suppression, in which it is typically difficult to determine the seizure duration.

The Determination of the Duration of ElectroconvulsiveTherapy-Induced Seizure Using Local Standard Deviationof the Electroencephalogram Signal and the Changesof the RR Interval of Electrocardiogram

Objectives@#ZZIn electroconvulsive therapy (ECT) research and practice, the precise determination of seizure duration is importantin the evaluation of clinical relevance of the ECT-induced seizure. In this study, we have developed computerized algorithms to assessthe duration of ECT-induced seizure. @*Methods@#ZZSubjects included 5 males and 6 females, with the mean age of 33.1 years. Total 55 ECT sessions were included in theanalysis. We analyzed the standard deviation of a finite block of electroencephalography (EEG) data and the change in the local slope ofRR intervals in electrocardiography (ECG) signals during ECT-induced seizure. And then, we compared the calculated seizure durationsfrom EEG recording (EEG algorithm) and ECG recording (ECG algorithm) with values determined by consensus of clinicians basedon the recorded EEG (EEG consensus), as a gold standard criterion, in order to testify the computational validity of our algorithms. @*Results@#ZZThe mean seizure durations calculated by each method were not significantly different in sessions with abrupt flattenedpostictal suppression and in sessions with non-abrupt flattened postictal suppression. The intraclass correlation coefficients (95% confidenceinterval) of the three methods (EEG algorithm, ECG algorithm, EEG consensus) were significant in the total sessions [0.79(0.70–0.86)], the abrupt flattened postictal suppression sessions [0.84 (0.74–0.91)], and the non-abrupt flattened postictal suppressionsessions [0.67 (0.45–0.84)]. Correlations between three methods were also statistically significant, regardless of abruptness of transition. @*Conclusions@#ZZOur proposed algorithms could reliably measure the duration of ECT-induced seizure, even in sessions with nonabrupttransitions to flat postictal suppression, in which it is typically difficult to determine the seizure duration.

Differential Association of Adiposity Measures with Heart Rate Variability Measures in Koreans

PURPOSE: Although obesity has been associated with imbalances in cardiac autonomic nervous system, it is unclear whether there are differential relationships between adiposity measures and heart rate variability (HRV) measures. We aimed to examine differences in the relationship between adiposity measures and HRV indices in a healthy Korean population. MATERIALS AND METHODS: In all, 1409 non-smokers (811 males, 598 females) without known histories of cardiovascular (CV), endocrine, or neurological diseases underwent adiposity measurements [(body mass index (BMI), percentage of body fat mass (PBF), and waist-to-hip ratio (WHR)], the HRV assessment (SDNN, RMSSD, LF, HF, LF/HF, and pNN50), and examination for CV risk factors (fasting glucose, LDL-cholesterol, HDL-cholesterol, triglycerides, hs-CRP, and blood pressure). RESULTS: Compared with BMI and PBF, WHR was more strongly correlated with each HRV index and more likely to predict decreased HRV ( or =15 percentile of each HRV index) in ROC curves analysis. In linear regression analysis, all adiposity measures were inversely associated with each HRV measure before adjusting for age, gender, and CV risk factors (p or =25 kg/m2, but not for those with BMI <25 kg/m2. CONCLUSION: WHR and PBF appear to be better indicators for low HRV than BMI, and the association between abdominal adiposity and HRV may be stronger in overweight subjects.

Association of Heart Rate Variability with the Framingham Risk Score in Healthy Adults / 가정의학회지

BACKGROUND: The aim of this study was to investigate the relationship between heart rate variability (HRV), the Framingham risk score (FRS), and the 10-year risk of coronary heart disease (CHD) development among Korean adults. METHODS: The subjects were 85 healthy Korean adults recruited from a health check-up center. The FRS and 10-year risk of CHD development were calculated. RESULTS: The FRS in men was inversely correlated with the standard deviation of all normal to normal RR-intervals (SDNN); the root mean square successive difference (RMSSD); the percentage of successive normal cardiac inter-beat intervals greater than 20 ms, 30 ms, and 50 ms (pNN20, pNN30, pNN50); the low frequency (LF); and the high frequency (HF) (P or = 10%. CONCLUSION: This study therefore indicates that the HRV indices, particularly SDNN, RMSSD, pNN30, LF, and HF may be useful parameters for the assessment of CHD risk. Most notably, the usefulness of these HRV measures as indicators for CHD risk evaluation may be greater among men than among women.

Wearable Physiologic Monitoring System in Health Promotion

With the development of body sensor technology, wearable health monitoring systems have been an emerging information technology in the 'ubiquitous health care' system. Wearable sensors enable long-term continuous physiological monitoring important in health promotion and management of many chronic disorders. In this paper, we present several wearable health monitoring systems developed by different countries and discuss emerging opportunities, as well as, existing challenges such as standardization, administration, validation, and discrepancy issues between technology and clinical implication.

The pNNx Heart Rate Variability Statistics: An Application to Neuroautonomic Dysfunction of Clozapine-Treated Subjects

OBJECTIVE: The percentage of successive normal cardiac interbeat intervals greater than 50 msec (pNN50) is a widely used heart rate variability measure, which is useful in identifying the neuroautonomic dysfunction of psychiatric disorders. However, pNN50 is only one member of a larger family of pNNx statistics, where x is greater than 0 msec. The potential application of the general pNNx statistics has not yet been explored in the psychiatric field. The authors examined the pNNx statistics in clozapine-treated subjects and normal controls to evaluate the usefulness of the general pNNx statistics. METHODS: Sixty-one schizophrenic patients treated with clozapine and fifty-nine normal controls were evaluated. Probability values for the differences between the groups at each pNN value (range: pNN1-pNN100) were calculated using data obtained from a 30-minute electrocardiogram. RESULTS: The conventional pNN50 and pNNx values with x<50 msec were all significantly lower in the patient group (p<0.05). The distinction between the two groups was more prominent at pNN values less than 50 msec than that observed at pNN50. The maximum separation between groups occurred at pNN5 (68.2+/-19.1 vs. 22.5+/-20.5, p<10(-22)). CONCLUSION: The pNNx with x<50 msec provided more robust discrimination between the groups than the conventional pNN50, suggesting the importance of analyzing very small variations of interbeat interval in discriminating normal and pathological heart rate patterns. The results also suggest that the general pNNx statistics may be applied and useful in evaluating the neuroautonomic dysfunction in patients treated with clozapine, complementing the traditionally computed pNN50 value.

The pNNx Heart Rate Variability Statistics: An Application to Neuroautonomic Dysfunction of Clozapine-Treated Subjects

OBJECTIVE: The percentage of successive normal cardiac interbeat intervals greater than 50 msec (pNN50) is a widely used heart rate variability measure, which is useful in identifying the neuroautonomic dysfunction of psychiatric disorders. However, pNN50 is only one member of a larger family of pNNx statistics, where x is greater than 0 msec. The potential application of the general pNNx statistics has not yet been explored in the psychiatric field. The authors examined the pNNx statistics in clozapine-treated subjects and normal controls to evaluate the usefulness of the general pNNx statistics. METHODS: Sixty-one schizophrenic patients treated with clozapine and fifty-nine normal controls were evaluated. Probability values for the differences between the groups at each pNN value (range: pNN1-pNN100) were calculated using data obtained from a 30-minute electrocardiogram. RESULTS: The conventional pNN50 and pNNx values with x<50 msec were all significantly lower in the patient group (p<0.05). The distinction between the two groups was more prominent at pNN values less than 50 msec than that observed at pNN50. The maximum separation between groups occurred at pNN5 (68.2+/-19.1 vs. 22.5+/-20.5, p<10(-22)). CONCLUSION: The pNNx with x<50 msec provided more robust discrimination between the groups than the conventional pNN50, suggesting the importance of analyzing very small variations of interbeat interval in discriminating normal and pathological heart rate patterns. The results also suggest that the general pNNx statistics may be applied and useful in evaluating the neuroautonomic dysfunction in patients treated with clozapine, complementing the traditionally computed pNN50 value.

Fractal and Complexity Measures of Heart Rate Dynamics in Patients with Normal and Left Ventricular Dysfunction: The Role of New Noninvasive Markers for Cardiac Risk Stratification

BACKGROUND AND OBJECTIVES: The traditional indexes of heart rate (HR) variability may lack the ability to detect subtle, but important changes in HR behavior. Nonlinear heart rate variability (HRV) analysis methods that are based on chaos theory can reveal subtle abnormalities in the HR dynamics of patients with cardiovascular diseases. Therefore, we tested the validity of nonlinear analysis methods as markers to differentiate normal and abnormal HR dynamics in the cardiovascular disease state. SUBJECTS AND METHODS: One-hundred patients were studied: 70 patients with left ventricular dysfunction (LVD), including 40 post-myocardial infarct patients (PMI) and 30 dilated cardiomyopahty patients (DCM), and 30 age and gender-matched controls. One-hour, 6-hours (day and night each) and 24 hours of R-R interval data from 24-hour Holter recordings were subjected to the conventional time and frequency-domain analysis. The ApEn, short-term (alpha1) and long-term (alpha2) scaling exponents of the detrended fluctuation analysis (DFA) and the power-law exponent (beta) were also measured. RESULTS: Conventional linear measures did not show a significant difference except for the VLF, lnLF and the LF/HF ratio between the controls and the LVD patients. Among the analyzed parameters, beta, beta2 and alpha1 were the most powerful discriminators. The beta of the normal and LVD patients was -1.10+/-0.29 and -0.70+/-0.40, respectively (p<0.001), and the alpha1 was 1.08+/-0.23 and 0.81+/-0.28, respectively (p<0.001). The beta, beta2 and alpha1 can discriminate the etiologic cause of LVD. The length of the R-R interval data did not affect the result, and a significant correlation was observed. The individual values of the fractal and complexity measures were more stable than those of the conventional linear measures. CONCLUSION: We conclude that the measures derived from fractal and complexity methods are useful for detecting altered HR dynamics of LVD and for improving the shortcomings of the conventional measures.

Symbolic Analysis of Heart Rate Dynamics before the Spontaneous Onset of Paroxysmal Atrial Fibrillation

BACKGROUND AND OBJECTIVES: Heart rate variability (HRV) analysis, by conventional measures, for predicting the risk of atrial fibrillation (AF) has inherent shortcomings. Recently, nonlinear HRV analysis methods have been developed to reveal heart rate dynamics not evident from usual HRV measures. The purpose of this study was to test the hypothesis"heart rate dynamics are altered before the spontaneous onset of paroxysmal AF (PAF)"using algorithms derived from symbolic dynamics based on nonlinear system theory. SUBJECTS AND METHODS: This study included 34 subjects (30 males, 59+/-9 years): 17 PAF patients and 17 gender and age-matched controls, who underwent 24-hour Holter ECG. The dynamics of one hour of normal sinus rhythm before the onset of AF were assessed using 4 different symbolization algorithms, and quantified by Shannon entropy (SE) and Renyi entropy (RE). RESULTS: The SE, RE and Error-corrected SE (ECSE) were larger in the PAF than the control patients when the raw R-R data was assessed (Algorithm I). However, when reconstructed time series, expressed as the time difference between 2 successive R-R interval, were analyzed (Algorithm II, III and IV), the entropy of the PAF patients were consistently smaller than those of the controls. Of the 4 different symbolization algorithms, algorithms II and III showed a significant difference in the SE, ECSE and RE between the PAF and the control patients (p<0.05). The difference in the RE at q=4 was most significant (p<0.001). Of the various word patterns seen during analysis using algorithms II and III, a marker of heart rate variation, the frequency of (1,1,1) pattern, was two-fold higher than in the control patients. The frequency of this pattern was 1.5-fold higher in the PAF patients when algorithm IV was used. These results suggest that a few specific word patterns are repetitive in a pathologic condition, such as PAF, and the heart rate dynamics were decreased in PAF. CONCLUSION: HRV analysis by symbolic dynamics may be a useful adjunctive tool for the detection of abnormal heart rate dynamics as a pathophysiological mechanism of PAF.

Approximate Entropy of the Short-term Variability of Fetal Heart Rate as an Efficient Measurement of Fetal Distress / 대한산부인과학회잡지

OBJECTIVE: The purpose of this study was to evaluate the usefulness of approximate entropy on fetal heart rate variability of electronic fetal monitoring taken during antepartum and intrapartum periods as a new diagnostic method of fetal distress. METHODS: Among 76 pregnant women who underwent computerized electronic fetal monitoring and cord blood gas analysis, we divided them into 3 groups, i.e.; 36 into normal fetus group, 26 into presumed distress group and 14 into acidemic distress group. We performed a frequency analysis on time series of heart rate variability in three groups. In order to perform non-linear analysis on the raw data of the fetal heart rate, after resampling and low pass filtering, we investigated approximate entropy. RESULTS: The results of the approximate entropy showed that the value in normal fetus group was significantly high than the value in distress group. But in the distress group, ApEn value was not difference between acidemic and non-acidemic subgroup. ApEn of HRV was confirmed in nonlinear parameter without low pass filtering and resampling. CONCLUSION: The results show that the fetal heart rate variability has nonlinear characteristics and could distinguish normal fetal heart rate pattern and distress pattern numerically and objectively. And these ApEn value are useful for prediction and diagnosis of fetal distress in ante and prenatal periods.

Spatio-Temporal Distribution and Propagation of Temporal Lobe Seizures: Application of Nonlinear Mutual Cross Prediction

BACKGROUND: Nonlinear mutual cross prediction (MCP) characterizes dynamic interdependence among nonlinear systems. MCP also reveal relative strength of the coupling between systems, thus provides information about the direc-tion of interdependence. The aim of this study is to apply MCP algorithm to multi-channel EEG and to characterize spatio- temporal pattern of seizure. METHODS: We analyzed MCP of EEG of three medically intractable temporal lobe epilepsy patients, who underwent temporal lobectomy (left 2, right 1). Asymmetry of nonlinear cross predictability between channels was investigated. Five epochs of interictal EEG free from epileptiform discharge(s) and of ictal EEG were analyzed. RESULTS: In interictal period, both frontal and occipital region appeared a weak driving force while awake and this driving force was further weakened during sleep. Before the onset of the seizure (preictal phase), the intensity of driving system became slightly stronger around seizure foci in 3 out of 8 seizures while no significant change was seen on the naked eyes. However this change was dim and not continuous. At the onset of seizure (ictal phase), 5 out of 8 seizures showed strong driving force around seizure foci. Three seizures without significant change initially had strong driving force as synchronous seizure discharges became built-up and spreading to surrounding areas in the middle of seizure. All seizures showed ipsilateral frontotemporal strong driving force and centroparietal response system, which was typical spatio-temporal distribution of MCP. CONCLUSION: MCP analysis may be a useful method for detecting spatio-temporal distribution and propagation pattern in temporal lobe epilepsy.

Nonlinear Dynamic and Chaotic Analysis of Fetal Heart Rate in Fetal Distress / 대한산부인과학회잡지

OBJECTIVES: For estimating the antenatal fetal wellbeing to develop new analysis method of fetal heart rate(FHR) with electronic Fetal Heart Rate Monitoring(eFHRM) and computer. METHODS: Heart rate signal is received from distressed fetus using eFHRM. It is necessary to carry out low pass filtering as a preprocess for the nonlinear method. Nonlinear parameters are calculated and classified to investigate the relations between these parameters and values of umbilical cord blood gas. RESULTS: By dividing values of the umbilical cord blood gas into 5 fetuses of acidemic group and 17 fetuses of non-acidemic group after 22 neonates who presented fetal distress were born, the following results as compared with nonlinear chaotic analysis result were obtained. 1. Delay time through AMI for acidemic group was 16.80+/-3.11, and was higher than 15.41+/-2.27 for non-acidemic group, and is not significant in statistics. 2. Embedding Dimension calculated with FNN method was 5.60+/-2.07 for acidemic group, and 4.71+/-1.26 for non-acidemic group, and it was not significant statistically. 3. Correlation dimension for acidemic group was 1.41+/-0.20, and was higher than 1.10+/-0.38 for non-acidemic group, and is not significant in statistics. 4. Mean crossing value by isoangular return map was 28.80+/-11.34 for acidemic group, and 16.65+/-7.00 for non-acidemic group, and it was significant statistically(P=0.008). 5. In comparison of information entropy in 1-D ED, acidemic group was 6.32+/-0.38 and non-acidemic group was 6.20+/-0.28 and it was not significant statistically. Also, in comparison of value in 2-D ED, acidemic group was 10.20+/-0.34. It was higher than non-acidemic group of 9.51+/-0.43 significantly in statistics(P=0.004). But, in comparison of value in 2-D EP, acidemic group was 8.78+/-0.86 and non-acidemic group is of 9.22+/-0.74 and it wasn't significant statistically. And, 2-D ED(DI) value was 10.64+/-0.14 for acidemic group and 10.51+/-0.18 for non-acidemic group, and it wasn't significant statistically. CONCLUSIONS: By the above result, nonliner dynamics and chaotic analysis of heart rate data with computer can serve as a new diagnosis method which may estimate the fetal wellbeing with real time. Through further studies for establishment of diagnosis standard and computer programming, real time diagnosis method shall be applied to clinical practice.

The Effectiveness of Lowdose Gonadotropin-Releasing Hormone Agonist and high dose hMG after Estrogen-Progesterone therapy in poor responder group to ovarian hyperstimulation / 대한산부인과학회잡지

OBJECTIVE: To evaluate the efficacy of low dose gonadotropin releasing hormone agonist(GnRH-a) therapy combined with high dose human menopausal gonadotrpin(hMG) following estrogen & progesteron therapy for poor responders. METHODS: From May 1997 to Feb 1999, 36 patients who were defined as poor responders on previous consecutive two and more superovulation cycles were randomly allocated to lowdose GnRH-a short protocol with high dose hMG protocol pretreated with estrogen & progesterone(E/P therapy)(n=16)(study group) and the clomiphene citrate with hMG(n=20)(control group). All patients were planned to undergone in-vitro- fertilization(IVF) and embryo transfer(ET) after controlled ovarian hyperstimulation(COH). RESULTS: Two groups were similar with respect to clinical features and basal FSH and E2 levels. The mean level of E2 on day 5, 304.3+/-148.ng/ml in study group was significantly higher than that in control group, 182+/-34.9ng/ml. The mean levels of E2 on hCG day was also significantly higher in study group than control group(1324+/-320ng/ml, vs 414+/-168ng/ml). The mean day of hCG day in study group, 12.3+/-0.3 was shorter than that in control group, 13.8+/-0.4. The concellation rates of cycles were significantly lower in study group than control group(13.2% vs 84.2%). But clinical pregnancy rates did not showed the significant difference between two groups. CONCLUSION: The study suggested that a lowdose GnRH-a short protocol with high dose hMG pretreated with estrogen & progesterone can improve the ovarian response in poor responder group.

Nonlinear Analysis of Electroencephalogram during the Course of Electroconvulsive Therapy: A Single Case Study / 신경정신의학

OBJECTIVES: In order to search for new parameters for the evaluation of the adequacy of electroconvulsive therapy (ECT) the authors performed a non-linear analysis of electroencepha-logram(EEG)recorded during the course of electroconvulsive therapy(ECT)in a single female patient with depression. METHODS: Digitized EEG recordings from two ECT sessions spaced one week were analyzed at five different stages; pretreatment stable, postanesthetic-preictal, ictal, postictal suppression and posttreatment stable stages. RESULTS: Our analysis showed that 1)EEG signals had low dimensional (below 10 dimensions) deterministic characteristics 2) although EEG was nonstationary signal, non-linear parameters could reliably differentiate between various stages we examined. 3)the deterministic property of ictal EEG increased according to the progression of sessions and 4)the primary Lyapunov exponent(PLE)and correlation dimension of pre- and post-treatment stable stage EEG increased according to the progression of sessions. CONCLUSION: In this single case study, results of various non-linear analyses suggested that non-linear variables extracted from EEG recordings during ECT may have utilities as tools for the quantitative evaluation of ECT.