Nonlinear analysis of heart rate variability of healthy subjects and patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is one of the causes of mortality worldwide with an increasing prevalence. Heart rate variability (HRV) reflects the regulation mechanism of the cardiac activity by the autonomic nervous system. The assessment of HRV by using nonlinear methods is more sensitive for the detection of complexity when compared to linear methods. This study aims to get information about the autonomic dysfunction occurred in patients with COPD by analysing the complexity of HRV. Electrocardiogram signals recorded from healthy subjects, patients with moderate COPD and severe COPD (eight subjects per group) were analysed. The HRV signals were acquired from ECG signals. Signals were reconstructed in the phase space and largest Lyapunov exponent (LLE), correlation dimension, Hurst exponent and approximate entropy (ApEn) values were calculated. It has seen that for the patients with COPD LLE, correlation dimension, Hurst exponent and ApEn values were less than control group. According to this, HRV complexity decreases in the presence of COPD. However, there is no significant difference between COPD groups and the severity of COPD has no effect on the chaoticity of the system. The results revealed that autonomic dysfunction occurred in patients with COPD is associated with reduced HRV complexity.     

犬急性心肌梗死后HRV的非线性动力学分析

目的：观察心肌梗塞后非线性动力学参数的变化。方法：基于心肌梗塞的动物实验模型,通过心电采集,记录和预处理,用非线性动力学方法分析RR间期序列,并用单光子发射计算机断层成像实验方法进行比较,结果：急性心肌梗塞后关联维数和近似熵都减少,且15天后又逐渐恢复,急性心肌梗死后李氏指数增加,且随着时间的推移逐渐恢复到正常,结论：非线性动力学参数可以反应心肌缺血的程度和急性心肌缺血后的恢复情况。     

Multiscale Analysis of Heart Rate Variability: A Comparison of Different Complexity Measures

Heart rate variability (HRV) is an important dynamical variable of the cardiovascular function. There have been numerous efforts to determine whether HRV dynamics are chaotic or random, and whether certain complexity measures are capable of distinguishing healthy subjects from patients with certain cardiac disease. In this study, we employ a new multiscale complexity measure, the scale-dependent Lyapunov exponent (SDLE), to characterize the relative importance of nonlinear, chaotic, and stochastic dynamics in HRV of healthy, congestive heart failure (CHF), and atrial fibrillation subjects. We show that while HRV data of all these three types are mostly stochastic, the stochasticity is different among the three groups. Furthermore, we show that for the purpose of distinguishing healthy subjects from patients with CHF, features derived from SDLE are more effective than other complexity measures such as the Hurst parameter, the sample entropy, and the multiscale entropy.     

Predicting depressed patients with suicidal ideation from ECG recordings

Globally suicidal behavior is the third most common cause of death among patients with major depressive disorder (MDD). This study presents multi-lag tone–entropy (T–E) analysis of heart rate variability (HRV) as a screening tool for identifying MDD patients with suicidal ideation. Sixty-one ECG recordings (10 min) were acquired and analyzed from control subjects (29 CONT), 16 MDD subjects with (MDDSI+) and 16 without suicidal ideation (MDDSI?). After ECG preprocessing, tone and entropy values were calculated for multiple lags (m: 1–10). The MDDSI+ group was found to have a higher mean tone value compared to that of the MDDSI? group for lags 1–8, whereas the mean entropy value was lower in MDDSI+ than that in CONT group at all lags (1–10). Leave-one-out cross-validation tests, using a classification and regression tree (CART), obtained 94.83 % accuracy in predicting MDDSI+ subjects by using a combination of tone and entropy values at all lags and including demographic factors (age, BMI and waist circumference) compared to results with time and frequency domain HRV analysis. The results of this pilot study demonstrate the usefulness of multi-lag T–E analysis in identifying MDD patients with suicidal ideation and highlight the change in autonomic nervous system modulation of the heart rate associated with depression and suicidal ideation.     

用于刺激条件下自主神经功能评定的心率变异性分析系统

作者介绍一种心率变异性（ＨＲＶ）分析系统。该系统由心电放大器、Ａ／Ｄ转换器、心律失常分析、ＨＲＶ分析等模块组成，能对被检测对象提供定量的时域和频域分析结果，并能以Ｌｏｒｅｎｚ散点图、Ｒ－Ｒ间期分布图等更直观的图形形式显示分析结果。本系统的研究目的在于结合其它临床检查方法为空军选拔飞行员、飞行人员医学鉴定提供一种客观的、定量的自主神经功能评价方法，同时也为临床提供一种可行的ＨＲＶ检测手段。     

Variability of QT interval duration in obstructive sleep apnea: an indicator of disease severity

STUDY OBJECTIVE: To determine OSA-related changes in variability of QT interval duration and in heart rate variability (HRV), and to evaluate the relationship of these parameters to disease severity. DESIGN: Retrospective analysis of diagnostic sleep records. SETTINGS: Clinical sleep laboratory in a hospital setting. PATIENTS: Twenty patients (12 males and 8 females) without significant comorbidities who were undergoing polysomnography were studied. MEASUREMENTS AND RESULTS: Standard heart rate variability measures and QT variability (Berger algorithm) were computed over consecutive 5-minute ECG epochs throughout the night. The effect of sleep stage and the relationship between these parameters and the severity of OSA as determined by the respiratory disturbance index (RDI) were explored. Further, a linear regression model of QT variability was developed. Severity of OSA (RDI) was 49 +/- 28 (range from 17-107) events/ hr. QT variability was the only ECG measure significantly correlated with RDI (both log-transformed; r = 0.6, P = 0.006). Further, QT variability was correlated with the minimum oxygen saturation (r = -0.55, P = 0.01). Sleep stage showed a significant effect on HRV, but not on QT variability. In the regression model, RDI was the strongest predictor of QT variability (R2 increase 38%), followed by high and low frequency power of HRV (R2 increase 10% each). CONCLUSION: Obstructive sleep apnea is associated with changes in QT interval variability during sleep. The variance of beat-to-beat QT intervals correlates more strongly with the severity of OSA (as determined by RDI) than standard measures of heart rate variability, and is correlated with blood oxygenation, but not sleep stage.     

基于非线性动力学和高斯混合模型/支持向量机的病态嗓音识别与研究

传统的病态嗓音的识别研究中,通常采用线性分析技术分析嗓音的特性,将嗓音产生过程用一个经典的线性模型来近似,然而,这样却忽略了嗓音产生过程中的非线性特性。本文基于非线性动力学的分析方法,定量分析并提取了嗓音的7维非线性特征——Hurst参数、时间延迟、第二阶Rényi熵、香农熵、关联维、Kolmogorov熵(K熵)、最大Lyapunov指数。实验结果表明,非线性动力学的方法能够弥补传统分析方法的不足,较好分析正常与病态嗓音;应用高斯混合模型(GMM)和支持向量机(SVM)的模式识别方法,分别对测试集39例正常嗓音和36例病态嗓音进行识别,均得到较好的识别率,分别为97.22%和97.30%。     

心率变异和RT变异频域分析的方法学研究

心率变异作为检测自主神经系统功能平衡状态的无创性指标，日益受到重视，已成为心电信号处理中的研究热点之一。ＱＴ是心室肌复极化时间，从另一方面来反映自主神经系统的平衡状态。ＱＴ变异分析在临床应用上与心率变异分析是否有互补作用，目前这方面研究工作开展得不多。由于ＱＴ间期检测困难，一般以ＲＴ间期代替ＱＴ间期。建立了心率变异和ＱＴ变异测定方法。在采集２４ｈ心电信号后，首先要完成标志点的检测。较好地实现了心电Ｒ波标志点的检测和异位心跳的剔除，并采用以相关系数为条件的模板匹配方法检测出Ｔ波标志点。频域分析方法分别通过快速傅里叶变换法（ＦＦＴ）和自回归谱估计法（ＡＲ）实现了２４ｈ三维频谱显示图以及２４ｈＨＦ／ＬＦ和高频能量变化趋势图。以不同的频率控制受试者的呼吸，采集其心电数据，从ＲＲ间期和ＲＴ间期谱分析的结果可以看到，高频峰受到呼吸频率的调制，高频峰可能与迷走神经活动有关。这一过程也检验了心电信号采集、检测和谱分析方法的可靠性。建立的方法为今后进一步深入研究打下了基础。随着心率变异和ＱＴ变异的检测和分析技术的日趋成熟，一定会在一些疾病的早期诊断、监护及预后评估等方面发挥更大的作用     

A comparison of photoplethysmography and ECG recording to analyse heart rate variability in healthy subjects

Measures of heart rate variability (HRV) are widely used to assess autonomic nervous system (ANS) function. The signal from which they are derived requires accurate determination of the interval between successive heartbeats; it can be recorded via electrocardiography (ECG), which is both non-invasive and widely available. However, methodological problems inherent in the recording and analysis of ECG traces have motivated a search for alternatives. Photoplethysmography (PPG) constitutes another means of determining the timing of cardiac cycles via continuous monitoring of changes in blood volume in a portion of the peripheral microvasculature. This technique measures pulse waveforms, which in some instances may prove a practical basis for HRV analysis. We investigated the feasibility of using earlobe PPG to analyse HRV by applying the same analytic process to PPG and ECG recordings made simultaneously. Comparison of 5-minute recordings demonstrated a very high degree of correlation in the temporal and frequency domains and in nonlinear dynamic analyses between HRV measures derived from PPG and ECG. Our results confirm that PPG provides accurate interpulse intervals from which HRV measures can be accurately derived in healthy subjects under ideal conditions, suggesting this technique may prove a practical alternative to ECG for HRV analysis. This finding is of particular relevance to the care of patients suffering from peripheral hyperkinesia or tremor, which make fingertip PPG recording impractical, and following clinical interventions known to introduce electrical artefacts into the electrocardiogram.     

Multiscale entropy and detrended fluctuation analysis of QT interval and heart rate variability during normal pregnancy

Pregnancy leads to physiological changes in various parameters of the cardiovascular system. The aim of this study was to investigate longitudinal changes in the structure and complexity of heart rate variability (HRV) and QT interval variability during the second half of normal gestation. We analysed 30-min high-resolution ECGs recorded monthly in 32 pregnant women, starting from the 20th week of gestation. Heart rate and QT variability were quantified using multiscale entropy (MSE) and detrended fluctuation analyses (DFA). DFA of HRV showed significantly higher scaling exponents towards the end of gestation (p<0.0001). MSE analysis showed a significant decrease in sample entropy of HRV with progressing gestation on scales 1-4 (p<0.05). MSE analysis and DFA of QT interval time series revealed structures significantly different from those of HRV with no significant alteration during the second half of gestation. In conclusion, pregnancy is associated with increases in long-term correlations and regularity of HRV, but it does not affect QT variability. The structure of QT time series is significantly different from that of RR time series, despite its close physiological dependence.     

Levels of agreement for RR intervals and short-term heart rate variability obtained from the Polar S810 and an alternative system

The aim of this study was to assess the agreement between HRV measures derived from a time series of RR intervals recorded by a standard 12-lead ECG (CP) and a commercially available RR interval recorder (S810). Thirty-three participants (19 males) (median age 36, range 20-63) underwent simultaneous, 5-min, supine RR-interval recordings. Each RR interval time series was analysed using the software supplied with the recording equipment. Two comparisons were then made. First, a comparison of RR interval data recording and editing only was made. Second, comparisons were made for measures of HRV derived from edited RR interval data. Agreement between RR intervals and standard HRV measures were assessed using intraclass correlation coefficient and limits of agreement. Agreement of HRV measures derived from RR intervals recorded and edited by individual systems was not acceptable. Agreement analyses for the number of RR intervals recorded and edited by each systems software showed excellent intraclass correlation coefficients (ICC lower 95% CI > 0.75) and acceptably narrow limits of agreement (LoA). These data indicate that the number of RR intervals recorded by S810 can agree well those recorded from a standard 12-lead ECG. This is true even after application of system specific data editing procedures. Commercial RR-interval recorders may offer a simple, inexpensive alternative to full 12-lead ECG in the recording and editing of RR intervals for subsequent HRV analysis in healthy populations.     

Assessment of heart rate variability derived from finger-tip photoplethysmography as compared to electrocardiography

Heart rate variability (HRV) is traditionally derived from RR interval time series of electrocardiography (ECG). Photoplethysmography (PPG) also reflects the cardiac rhythm since the mechanical activity of the heart is coupled to its electrical activity. Thus, theoretically, PPG can be used for determining the interval between successive heartbeats and heart rate variability. However, the PPG wave lags behind the ECG signal by the time required for transmission of pulse wave. In this study, finger-tip PPG and standard lead II ECG were recorded for five minutes from 10 healthy subjects at rest. The results showed a high correlation (median = 0.97) between the ECG-derived RR intervals and PPG-derived peak-to-peak (PP) intervals. PP variability was accurate (0.1 ms) as compared to RR variability. The time domain, frequency domain and Poincaré plot HRV parameters computed using RR interval method and PP interval method showed no significant differences (p < 0.05). The error analysis also showed insignificant differences between the HRV indices obtained by the two methods. Bland-Altman analysis showed high degree of agreement between the two methods for all the parameters of HRV. Thus, HRV can also be reliably estimated from the PPG based PP interval method.     

Comparison of three mobile devices for measuring R–R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system

The first aim of this study was to compare an ambulatory five-lead ECG system with the commercially available breast belt measuring devices; Polar S810i and Suunto t6, in terms of R–R interval measures and heart rate variability (HRV) indices. The second aim was to compare different HRV spectral analysis methods. Nineteen young males (aged between 22 and 31 years, median 24 years) underwent simultaneous R–R interval recordings with the three instruments during supine and sitting rest, moderate dynamic, and moderate to vigorous static exercise of the upper and lower limb. For each subject, 17 R–R interval series of 3-min length were extracted from the whole recordings and then analyzed in frequency domain using (1) a fast Fourier transform (FFT), (2) an autoregressive model (AR), (3) a Welch periodogram (WP) and (4) a continuous wavelet transform (CWT). Intra-class correlation coefficients (ICC) and Bland–Altman limits of agreement (LoA) method served as criteria for measurement agreement. Regarding the R–R interval recordings, ICC (lower ICC 95% confidence interval >0.99) as well as LoA (maximum LoA: −15.1 to 14.3 ms for ECG vs. Polar) showed an excellent agreement between all devices. Therefore, the three instruments may be used interchangeably in recording and interpolation of R–R intervals. ICCs for HRV frequency parameters were also high, but in most cases LoA analysis revealed unacceptable discrepancies between the instruments. The agreement among the different frequency transform methods can be taken for granted when analyzing the normalized power in low and high frequency ranges; however, not when analyzing the absolute values.     

Fear induced complexity loss in the electrocardiogram of flight phobics: a multiscale entropy analysis

In this study we explored the changes in the variability and complexity of the electrocardiogram (ECG) of flight phobics (N=61) and a matched non-phobic control group (N=58) when they performed a paced breathing task and were exposed to flight related stimuli. Lower complexity/entropy values were expected in phobics as compared to controls. The phobic system complexity as well as the heart rate variability (HRV) were expected to be reduced by the exposure to fearful stimuli. The multiscale entropy (MSE) analysis revealed lower entropy values in phobics during paced breathing and exposure, and a complexity loss was observed in phobics during exposure to threatening situations. The expected HRV decreases were not found in this study. The discussion is focused on the distinction between variability and complexity measures of the cardiac output, and on the usefulness of the MSE analysis in the field of anxiety disorders.     

Assessment of heart rate variability derived from finger-tip photoplethysmography as compared to electrocardiography

Heart rate variability (HRV) is traditionally derived from RR interval time series of electrocardiography (ECG). Photoplethysmography (PPG) also reflects the cardiac rhythm since the mechanical activity of the heart is coupled to its electrical activity. Thus, theoretically, PPG can be used for determining the interval between successive heartbeats and heart rate variability. However, the PPG wave lags behind the ECG signal by the time required for transmission of pulse wave. In this study, finger-tip PPG and standard lead II ECG were recorded for five minutes from 10 healthy subjects at rest. The results showed a high correlation (median = 0.97) between the ECG-derived RR intervals and PPG-derived peak-to-peak (PP) intervals. PP variability was accurate (0.1 ms) as compared to RR variability. The time domain, frequency domain and Poincaré plot HRV parameters computed using RR interval method and PP interval method showed no significant differences (p < 0.05). The error analysis also showed insignificant differences between the HRV indices obtained by the two methods. Bland-Altman analysis showed high degree of agreement between the two methods for all the parameters of HRV. Thus, HRV can also be reliably estimated from the PPG based PP interval method.     

Prognostic value of heart rate variability after myocardial infarction. A comparison of different data-processing methods

Reduced heart rate variability (HRV) has been reported as a predictor of mortality in recent myocardial infarction patients. However, its automated assessment in long-term ECG recordings is complicated by recording noise and beat-recognition errors which necessitate filtering of the computer-established sequence of beat-to-beat intervals, and visual checking and manual editing of the long-term recordings, making the whole method operator-dependent. To develop a fully automated method for analysis of HRV from 24 h ECG recordings, five filtering algorithms were combined with three methods of expressing HRV numerically and used to compare two groups of patients undergoing 24 h tape recordings of the ECG within the first two weeks after myocardial infarction. One group comprised 15 patients who later suffered death or ventricular tachycardia, the other group comprised 15 randomly selected uncomplicated cases. Using the same two groups of patients, three different methods of expressing HRV on a beat-to-beat basis were also compared empirically. The results show that alternative, operator-independent methods for establishing HRV from continuous long-term ECG recordings of postmyocardial infarction patients seem to be as effective as previously reported methods which rely on operator-dependent data post-processing techniques.     

Recording of ECG signals on a portable MiniDisc recorder for time and frequency domain heart rate variability analysis

Analysis of heart rate variability (HRV) is a non-invasive technique useful for investigating autonomic function in both humans and animals. It has been used for research into both behaviour and physiology. Commercial systems for human HRV analysis are expensive and may not have sufficient flexibility for appropriate analysis in animals. Some heart rate monitors have the facility to provide inter-beat interval (IBI), but verification following collection is not possible as only IBIs are recorded, and not the raw electrocardiogram (ECG) signal. Computer-based data acquisition and analysis systems such as Po-Ne-Mah and Biopac offer greater flexibility and control but have limited portability. Many laboratories and veterinary surgeons have access to ECG machines but do not have equipment to record ECG signals for further analysis. The aim of the present study was to determine whether suitable HRV data could be obtained from ECG signals recorded onto a MiniDisc (MD) and subsequently digitised and analysed using a commercial data acquisition and analysis package. ECG signals were obtained from six Thoroughbred horses by telemetry. A split BNC connecter was used to allow simultaneous digitisation of analogue output from the ECG receiver unit by a computerised data acquisition system (Po-Ne-Mah) and MiniDisc player (MZ-N710, Sony). Following recording, data were played back from the MiniDisc into the same input channel of the data acquisition system as previously used to record the direct ECG. All data were digitised at a sampling rate of 500 Hz. IBI data were analysed in both time and frequency domains and comparisons between direct recorded and MiniDisc data were made using Bland-Altman analysis. Despite some changes in ECG morphology due to loss of low frequency content (primarily below 5 Hz) following MiniDisc recording, there was minimal difference in IBI or time or frequency domain analysis between the two recording methods. The MiniDisc offers a cost-effective approach to intermediate recording of ECG signals for subsequent HRV analysis and also provides greater flexibility than use of human Holter systems.     

Detection of asphyxia using heart rate variability

The long-term aims of this study are to find a parameter derived from the ECG that has a high sensitivity and specificity to asphyxia and, once we know or suspect that asphyxia occurred, to estimate how severe it was. We carried out a pilot study in which 24 adult Wistar rats were anaesthetised and subjected to controlled asphyxia for specified durations. We measured the pH, ‘neurological score’ and the ECG, extracting from this heart rate and heart rate variability (HRV). We have developed a technique capable of detecting asphyxia in less than 1 min, based on monitoring the ECG and estimating HRV by measuring the standard deviation of normal RR intervals (the RR interval is the time interval between two consecutive R-points of the QRS complex). In all cases the heart rate decreased and HRV increased, by an average of 46±33ms in relation to the baseline, at the onset of asphyxia. The comparison of the base level of HRV after and before asphyxia shows promise for the estimation of the severity of the episode; however, the limitations of this study should be noted as they include the small size of the cohort and the methods of analysis.     

Effects of long-term exercise training on cardiac autonomic nervous activities and baroreflex sensitivity

Reductions in tonic vagal controls of the heart and depressed baroreflex sensitivity (BRS) have been associated with a postural fall in blood pressure (BP) and the incidence of cardiac events among older people. We examined the hypothesis that BP regulation during orthostatic challenge as well as heart rate variability (HRV) at rest can be better maintained in long-term exercise-trained, healthy, older men (aged 60–70 years). Subjects were classified into two groups; long-term exercise-trained (LTET, n=14) and sedentary (SED, n=10) according to their history of physical activity. Prior to the dynamic BRS assessment, supine resting autonomic cardiac modulation was assessed by means of time domain HRV [standard deviation of ECG R–R interval (RRISD) and the coefficient of variation (CV)]. The BRS was assessed during 60° head-up tilting by simultaneously measuring beat-by-beat systolic blood pressure (SBP) and ECG R–R interval changes. The BRS gain was determined by the regression slope coefficient based on the extent of the SBP fall and the corresponding ECG R–R shortening during the orthostatic challenge. The results indicated that the LTET group manifested greater ECG R–R interval fluctuations with significantly higher resting RRISD and CV, compared with the SED group [59.5 (10.4) versus 27.7 (7.8) ms, p<0.05; 5.5 (0.8) versus 2.8 (0.7)%, p<0.05], respectively. Using dynamic BRS testing during the acute orthostatic challenge, the LTET group showed a significantly higher BRS gain than the SED [6.4 (0.8) versus 3.8 (0.6) ms·mmHg⁻¹, p<0.017] group. These results indicate that CV and BRS are well maintained in healthy, LTET older individuals when compared with their sedentary peers. Our data suggest that this augmented autonomic cardiac modulation reflects better parasympathetic responsiveness in LTET individuals. Data provide further support for long-term exercise training as another possible cardioprotective factor that might decrease susceptibility to ventricular fibrillation as well as assist arterial BP at the onset of an orthostatic challenge in older men. Electronic Publication     

中重度抑郁症患者心电图及心率变异性分析

目的:探讨中重度抑郁症患者心电图及心率变异性特点,为临床评估中重度抑郁症心脏自主神经功能变化提供依据.方法:选择2018年6月至2019年12月就诊于湖南省脑科医院的中重度抑郁症患者38例为研究组,32例健康志愿者为对照组,比较两组心电图异常率及心率变异性,并统计分析各指标之间的差异.结果:研究组心电图异常ST-T改变...