Non-linear analysis of heart rate variability during deep breathing at 0.1 Hz frequency

Background: Heart rate variability (HRV) analysis is an important tool to assess the cardiac autonomic regulation in health and disease. Time-domain and frequency-domain analyses are linear methods that are traditionally used for HRV analysis. Application of non-linear methods in HRV analysis has been shown to provide additional information and has been found to be useful in predicting complications and mortality in cardiovascular disease conditions. HRV analysis during deep breathing is commonly used to assess the integrity and extent of the parasympathetic control of the heart. Aim and Objectives: This study aims to analyze the HRV during deep breathing at 0.1 Hz frequency, 6 breaths/minute using non-linear methods and to see whether they correlate with the time-domain measures of HRV. Materials and Methods: Twelve healthy volunteers performed deep slow breathing at 0.1 Hz frequency for 5 min following recorded prompts. In the time domain, mean heart rate (MHR), SDNN, RMSSD, and pNN50 during baseline and deep breathing were measured. In the non-linear domain, approximate entropy (AppEn), sample entropy (SampEn), and detrended fluctuation analysis DFA (?1) were calculated. The quantitative measures of the Poincare plot, namely, SD1, SD2, and SD2/SD1, which are known to provide linear information, were also estimated. Wilcoxon’s signed-rank test was used to compare the baseline parameters with those of deep breathing. Spearman’s correlation was used to assess the correlation between the parameters obtained from the different methods. Results: There was no significant change in the MHR, RMSSD, pNN50, and SD1 during 0.1 Hz deep breathing while SDNN, SD2, SD2/SD1, and DFA?1 showed a significant increase. Furthermore, 0.1 Hz breathing decreased the AppEn and SampEn measures of HRV. There was a strong correlation among SDNN, RMSSD, pNN50, SD1, SD2, SD2/SD1, and DFA?1, but there was no correlation between any of the above measures and the non-linear measures AppEn and SampEn. Conclusion: While the non-linear measure DFA?1 correlates well with time domain measures of HRV and the quantitative measures of the Poincare plot during 0.1 Hz breathing, AppEn and SampEn do not show such correlation. Instead, they decrease significantly when breathing is voluntarily controlled at 6 breaths/min.

Application of heart rate variability in acupuncture research / 针刺研究

The measurement of heart rate variability (HRV) has the advantages of noninvasiveness and simple operation and is widely used in clinical trials and scientific research for assessing reactions of the autonomic nervous system. More and more studies on acupuncture also take HRV as an important index. In addition to the definition, origin, analytical methods, and significance of time domain and frequency domain parameters of HRV, we reviewed the situations of application of HRV to acupuncture research in recent years, analyzed the influence of acupuncture and sham acupuncture, different acupuncture methods, and different acupoints on HRV, and confirmed the role of HRV in reflecting the effect of acupuncture on the vagal and sympathetic systems. However, various interference factors for HRV measurement and diverse methods for data analysis may lead to great differences in the experimental results of HRV and the interpretation of parameters. Therefore, careful analysis is needed in future studies on acupuncture with HRV as an observation index.

Fatigue analysis system with HR and HRV as indexes / 医疗卫生装备

In this paper,heart rate (HR) and heart rate variability (HRV) are extracted from ECG,and the five indexes in both time and frequency domains are analyzed.The result shows that the standard deviation (SDNN) of R-R intervals,the value of total power (TP),the power value of low frequency (LF) of HRV and the value of LF/HF increase obviously,while the power value of high frequency (HF) decreases markedly after fatigue.The physical fatigue level is classified according to the rate of increase and decrease of the indexes above.It is suggested that these five ECG indexes be used to reflect and evaluate the degree of physical fatigue quantitatively.

Linear and Nonlinear Analysis of Heart Rate Variability in Postoperative Myocardial Ischemic Patients: Time Domain Analysis versus Approximate Entropy / 대한마취과학회지

BACKGROUND: Postoperative myocardial ischemia has been regarded as one of the major predictors of adverse cardiac outcomes after noncardiac surgery in high risk patients. Many schemes have been proposed to stratify the potential risk of this patient group in more noninvasive and cost-effective ways and analysis of heart rate variability (HRV) is one of them. To uncover the underlying changes in HRV with postoperative myocardial ischemia five analytical methods were introduced; SDNN (standard deviation of normal to normal intervals), SDANN (standard deviation of the mean of normal RR intervals for each 5 min period of the entire electrocardiographic recording), RMSSD (root mean square successive difference, the squre root of the mean of the sum of the squares of differences between adjacent normal RR intervals over the entire electrocardiographic recording), PNN50 (percent of difference between adjacent normal RR intervals that are greater than 50 ms computed over the entire electrocardiographic recording) for linear time domain analysis and approximate entropy for nonlinear complexity analysis. METHODS: Sixteen vascular surgical patients were monitored by an ambulatory electrocardiogram preoperatively and during the first postoperative day (POD1). HRV values analyzed by five different measures were compared between a control group (C group) of eight patients with no postoperative ischemia and a postoperative ischemic group (PI group) of eight with ischemia on POD1. RESULTS: Approximate entropy was the only measure of HRV which was significantly lower in PI group than that of C group (P< 0.01) on POD1. CONCLUSIONS: Approximate entropy, a complexity measure could provide more sensitive information about the physiologic changes associated with postoperative ischemia which could not be obtained from the conventional HRV measures. Time domain analyses can be used as adjuvant measures providing information about the cardiac autonomic regulation.

Analysis of Heart Rate Variability in Preoperative Diabetic Patients by Linear and Nonlinear Dynamics / 대한마취과학회지

BACKGROUND: The aim of this study was to investigate the underlying changes in heart rate variability (HRV) of preoperative diabetic patients using five analytical methods; SDNN (standard deviation of normal to normal intervals), SDANN (standard deviation of the mean of normal RR intervals for each 5 min period of the entire electrocardiographic recording), RMSSD (root mean square successive difference, the squre root of the mean of the sum of the squares of differences between adjacent normal RR intervals over the entire electrocardiographic recording), PNN50 (percent of difference between adjacent normal RR intervals that are greater than 50 ms computed over the entire electrocardiographic recording) for linear time domain analysis and approximate entropy for nonlinear complexity analysis. METHODS: HRV values analyzed by five different measures were compared between a control group of ten nondiabetics without any significant systemic disease and a diabetic group of ten patients from the preoperative ambulatory electrocardiographic recordings. RESULTS: Approximate entropy, SDNN and SDANN values were significantly lower in the diabetic group than those of the control group (P< 0.01). CONCLUSIONS: Significantly decreased approximate entropy, SDNN and SDANN could provide information about decreased cardiovascular complexity and sympathetic output, suggesting the nature of dysfunction of the diabetic cardiovascular system.

Signal Averaged Electrocardiography Using Holter Tape in Patients without Heart Disease

BACKGROUND: Ventrlcular tachyarrhythmias are major cause of sudden cardiac death in patients after myocardial infarction and their accurate detection seems to be important in prevention of sudden cardiac death. Clinical findings, treasmill test, holter monitoring and coronary angiography have been used to search for high risk group in sudden cardiac death. Recently electrographysiologic stimulation has been to this, but it is not practical, because of high cost and invasiveness. Signal averaged electrocardiogram(SAECG) may be helpful in prediction of high risk group in sudden cardiac death. So we try to know the values of SAECG in Korean patients without heart disease. RESULTS: 1) The mean value and standard deviation of Time domain analysis is as follows ; fQRS : 106.8+/-12.3ms, RMS : 36.2+/-21.5(micro)V, LAS : 27.2+/-8.1ms. 2) The mean value and standard deviation of Spectral turbulence analysis is a follows ; LSCR : 58.6+/-3.9, ISCM : 95.2+/-0.8, ISCSD : 71.8+/-15.7, SE : 6.9+/-1.8. CONCLUSION: There was no significant difference between male and female. Time domain analysis shows significant differences among each hour but spectral turbulence analysis did not. Spectral turbulence analysis shows high specificity.

Comparative Study of Signal-Averaged Electrocardiogram between Time Domain Analysis and Spectral Turbulence Analysis by 24-hr Holter Monitoring / 대한내과학회지

OBJECTIVES: Signal-averaged electrocardiography (SAECG) has been found to be a useful noninvasive technique for identifying patients at risk for life-threatening ventricular tachycardia. Delayed and fragmented activation of abnormal myocardial tissues causes the occurrence of high frequency low amplitude (HFLA) electocardiographic signals or late potentials. Generally, there are two methods in analyzing signal-averaged electrocardiography. Late potentials in the time domain analysis do not provide sufficient diagnostic power with regard to life-threatening Ventricular tachycardia. Buckingham et al. (1989) reported a time-domain sensitivity of 62%, a specificity of 75%. Spectral turbulence analysis (STA) of the signal-averaged ECG is the most recent frequency domain technique to improve the time domain sensitivity and specificity. So, We designed the study to compare the efficacy of Time Domain Analysis and Spectral Turbulence Analysis among five groups (Normal control, QRS widening, Postmyocardial infarction, Frequent VPC's with group beats, Nonsustained ventricular tachycardia). METHODS: 88 patients were selected from the patients who had been admitted between January 1994 and October l994, at National Medical Center. Patients were divided into five groups, which were respectively, Group A: Normal control group (n=33), Group B: QRS widening group (n=14), Group C: Postmyocardial infarction group (n=10), Group D: Frequent VPC's with group beats (n=22), Group E: Nonsustained VT group (n=9). We compared Spectral Turbulence Analysis and Time Domain Analysis of Signal-Averaged Electrocardiogram by 24 hours-Holter monitoring. RESULTS: 1) In normal control group(Group A), 9.1%(3 patients) were positive by Time Domain Analysis, but, all were negative by Spectral Turbulence Analysis. 2) In QRS widening group (Group B), 71.4%(10 patients) were positive by Time Domain Analysis, but, all were negative by Spectral Turbulence Analysis. 3) In postmyocardial infarction group (Group C), 309o were positive by Time Domain Analysis, and 10% were positive by Spectral Turbulence Analysis. 4) In frequent VPC's group (Group D), 22.7% (5 patients) were positive by Time Domain Analysis, and, 4.5%(1 patient) was positive by Spectral Tur-bulence Analysis. 5) In Nonsustained VT group (Group E), 33.3% (3 patients) were positive by Time Domain Analysis, and 11.1% (1 patient) was positive by Spectral Turbulence Analysis. CONCLUSIONS: In Time Domain Analysis, abnormal results were presented at Group R (QRS widening group) by 71.4%, which was markedly higher than other groups. But, in Spectral Turbulence Analysis, abnormal results were not presented at Group A and Group B. In Group A and Group B, Spectral Turbulence Analysis shows less false positive results than Time Domain Analysis.

Study on the interrelationship between time domain analysis of heart rate variability and chronic renal failure / 第二军医大学学报

Objective: To assess the autonomic nervous impairment in chronic renal failure and its related factors. Methods: Forty adults were randomly selected including in patients in the nephrology ward and healthy subjects for routine medical examination. The subjects were classified into 4 groups: normal subjects(NS),normal renal function,nitremia, uremic patients. The time domain measurements of heart rate variability(HRV) and ambulatory blood pressure were analyzed simultaneously . Results: (1) There were significant differences as compared with normal subjects in the time domain measurements of HRV in uremic group. It decreased significantly when the patient was defined as end stage chronic renal failure. There were no significant differences between NS,normal renal function group and nitremic group. (2) Time domain measurements of HRV was significantly lower( P