Evaluating the indicators of a heart rate variability analysis in dogs using Poincaré plots.

Heart rate variability analyses using Poincaré plots can be useful for evaluating the autonomic nervous system function. However, the interpretation of the quantitative indicators of Poincaré plots remains controversial. Thus, few studies have verified the effectiveness of the quantitative indicators in veterinary medicine. This study aimed to verify the reliability of Poincaré plot indicators using pharmacological models in dogs. Four healthy beagles were used in this study. Each dog was treated with propranolol, atropine, and propranolol-atropine to block the sympathetic, parasympathetic, and sympathetic-parasympathetic functions, respectively. The quantitative indicators of the Poincaré plots were calculated based on data from 300 electrocardiogram beats collected before and after the administration of each drug and statistically analysed. The quantitative indicators of the Poincaré plots, such as the standard deviation perpendicular to the major axis (SD1), standard deviation along the major axis (SD2), and SD1 × SD2, significantly decreased after the drug administration in both the parasympathetic and sympathetic-parasympathetic blockade models. However, no significant differences were observed in SD1/SD2 between the groups. The Poincaré plots reflected the changes in the autonomic nervous system of dogs. In dogs, SD1, SD2, and SD1 × SD2 can detect a state in which parasympathetic nerve activity is suppressed.

Social Buffering Effects during Craft Activities in Parallel Group Session Revealed by EEG Analysis and Parasympathetic Activity.

INTRODUCTION: The therapeutic structure of occupational therapy (OT) includes groups. Although the presence of others is expected to be relaxing due to the social buffering effect and the tend and befriend theory, it has not been sufficiently validated in accordance with the therapeutic structure of OT. The aim of this study was to investigate the electrophysiological evidence for the effectiveness of parallel groups and states of concentration on craft activities used in OT. METHODS: Thirty healthy young adults were used as controls to measure EEG and autonomic activity during craft activities in three conditions: alone, parallel, and nonparallel. EEG was analyzed using exact low-resolution electromagnetic tomography, and autonomic activity was analyzed using Lorenz plot analysis. RESULTS: Parasympathetic activity was significantly higher in the parallel condition than in the alone condition. A significant negative correlation was found between current source density and parasympathetic activity in the region centered on the right insular cortex in the α1 band, and functional connectivity in regions including the anterior cingulate cortex and insular cortex was associated with autonomic activity. CONCLUSION: Craft activities that occurred during frontal midline theta rhythm also increased parasympathetic activity. The results suggest that the parallel groups used in OT and the intensive state of craft activities induce a social buffering effect that increases parasympathetic activity despite the absence of physical contact or social support. This provides evidence for the effectiveness of the therapeutic structure of occupational activities and groups in OT.

Analysis of Poincaré plot derived from 5-min electrocardiography in dogs with myxomatous mitral valve disease.

BACKGROUND: Evaluation of heart rate variability (HRV) is used for risk assessment in a variety of cardiac diseases including myxomatous mitral valve degeneration (MMVD). OBJECTIVES: To compare the geometric analysis of HRV using visual patterns of Poincaré plot among different classes of MMVD in dogs and to analyse the differences in beat-to-beat variability using tachograms and sequential Poincaré plots among different shapes. ANIMALS AND METHODS: Healthy and MMVD dogs were retrospectively reviewed. Five-minute ECG data was used to create Poincaré plots and shapes were compared among groups. Furthermore, a sub-analysis of 50 consecutive R-R intervals was performed. Pearson Chi-square with adjusted standardized residuals was used to compare the categorical data between groups. RESULTS: Fifteen healthy dogs and 157 dogs with MMVD were included in the study. Normal and B1 groups showed a predominance of triangular shape (73% and 60% respectively; p < 0.05). In B2 group the predominant shape was comet (40%; p < 0.05) while comet and torpedo were predominant in Ca group (41% and 36% respectively; p < 0.05). Visual geometric analysis revealed a lower dispersion of the cloud clustering towards the left lower corner of the plot with MMVD progression. Diamond and triangle revealed a lower mean heart rate compared to comet and torpedo shapes (p < 0.01). Interclass correlation between 3 observers was 0.906 (95% CI of 0.8 - 0.96). CONCLUSIONS: Poincaré plot shape changes with MMVD progression suggesting that geometrical analysis of HRV in dogs with cardiac conditions could be a useful tool in the risk assessment and further studies are warranted.

The next heartbeat: Creating dynamic and histographic Poincaré plots for the assessment of cardiac rhythms.

The rhythm of the heart is not a stationary phenomenon, and therefore, incorporation of the dynamic Poincaré plot and tachogram provides additional diagnostic information to complement and expand waveform (P-QRST) analyses from the electrocardiogram. Although pattern assessment of the Poincaré plot and tachogram can provide an appraisal for normal and abnormal rhythms and serve as a potential means for machine-learned rhythm diagnoses, time-selected windows of beat-to-beat variability permit more detailed examination. As such, expanded criteria for rhythm diagnoses, identification of arrhythmic triggers, global appreciation of rhythm changes, and recognition of patterns that provoke mechanistic questions may be gleaned from the use of the methods reviewed in this report. More specifically, these methods demonstrate that limitations exist in the reliance on traditional measures of heart rate variability in the dog due to the non-linear beat-to-beat rhythm of sinus arrhythmia in the species. Behavior of arrhythmias based on coupling intervals, repeating patterns, preceding triggers of beat-to-beat variability, and circumstantial evidence of atrioventricular nodal conduction during atrial flutter and fibrillation are a few examples of discovery founded in these techniques. The open access website, The Next Heartbeat (https://thenextheartbeat.com/), permits anyone to implement these methods in the assessment of long-term electrocardiographic examinations (Holter monitoring) so that, as yet to be revealed, features of the beating heart through time may be discovered.

Optimal length of R-R interval segment window for Lorenz plot detection of paroxysmal atrial fibrillation by machine learning.

BACKGROUND: Heartbeat interval Lorenz plot (LP) imaging is a promising method for detecting atrial fibrillation (AF) in long-term monitoring, but the optimal segment window length for the LP images is unknown. We examined the performance of AF detection by LP images with different segment window lengths by machine learning with convolutional neural network (CNN). LP images with a 32 × 32-pixel resolution of non-overlapping segments with lengths between 10 and 500 beats were created from R-R intervals of 24-h ECG in 52 patients with chronic AF and 58 non-AF controls as training data and in 53 patients with paroxysmal AF and 52 non-AF controls as test data. For each segment window length, discriminant models were made by fivefold cross-validation subsets of the training data and its classification performance was examined with the test data. RESULTS: In machine learning with the training data, the averages of cross-validation scores were 0.995 and 0.999 for 10 and 20-beat LP images, respectively, and > 0.999 for 50 to 500-beat images. The classification of test data showed good performance for all segment window lengths with an accuracy from 0.970 to 0.988. Positive likelihood ratio for detecting AF segments, however, showed a convex parabolic curve linear relationship to log segment window length and peaked at 85 beats, while negative likelihood ratio showed monotonous increase with increasing segment window length. CONCLUSIONS: This study suggests that the optimal segment window length that maximizes the positive likelihood ratio for detecting paroxysmal AF with 32 × 32-pixel LP image is 85 beats.

Geometry of the Poincaré plot can segregate the two arms of autonomic nervous system - A hypothesis.

Autonomic Nervous System (ANS) operates to achieve the optimum physiological functioning and maintains homeostasis in a tonic and continuous manner. Evaluation of ANS profile is crucial in assessing autonomic dysfunction. Conventional ANS evaluation procedures fail to capture minute dynamic alterations of ANS activities. The ANS output pattern is appropriately reflected in the fine alteration of the resting heart rate (HR). HR is a non-stationary variable, results from the dynamic interplay between the multiple physiologic mechanisms. The control of cardiac rate or the chronotropic regulation of heart is considered as a coupled network of oscillators, each representing a specific facet of the cardiovascular reflex. The slower vasomotor oscillation via sympathetic system is combined with rapid respiratory oscillation by parasympathetic system to modulate the intrinsic oscillation pattern of the SA Node. Heart Rate Variability (HRV) is used to understand the autonomic influence on cardiovascular system in health and disease. Fourier decomposition of HRV offers us mainly two different frequency components. High frequency (HF) variation indicates parasympathetic variability due to respiration and Low frequency (LF) mainly implicates tonic sympathetic influence, due to slower vasomotor modulation of heart rate. However, different studies show conflicting results and direct recording of sympathetic nerve activity also failed to correlate with LF power in either healthy subjects or in patients with increased cardiac sympathetic drive. A scatter-plot where each R-R interval is plotted against the preceding R-R interval forms a distributed elliptic point cloud in two dimensional plane. The phase space realization of this plot with dimension two and delay one is referred to as Poincaré plot analysis, an emerging quantitative-visual technique where the shape of the plot is categorized into different functional classes. The plot provides summary as well as detailed beat-to-beat information of the heart. This plot can be extended to three dimensions and with multi-lag, offering more insight and information. A mathematical expression was developed by an interventional study by Toichi et al., using pharmacological blockers during different physiological variables that calculated the lengths of transverse and longitudinal axes of the Poincaré plot to derive two quantitative expressions of sympathetic and vagal influence on HRV: 'cardiac sympathetic index' (CSI)) and 'cardiac vagal index' (CVI). In the present study, we emulate Poincaré plot patterns seen in normal range of sympatho-vagal balances and also in Diabetes Mellitus (DM), known to cause autonomic dysfunction. The emerging pattern of R-R interval time series would provide valuable insight into the altered temporal dynamics and also extract crucial features embedded within. DM is a major public health crisis globally and particularly in Indian population. We hypothesize that, CSI and CVI will effectively segregate the two arms of ANS and can be utilized as an effective evaluation tool to explore the disease status in patients of Diabetes Mellitus. We also propose that, the dynamics of fluctuations in physiological rhythms that exhibit long-term correlation and memory, can also be explored and expressed quantitatively by incorporating various degrees of 'lag' in these recurrence plots.

The Use of Percent Change in RR Interval for Data Exclusion in Analyzing 24-h Time Domain Heart Rate Variability in Rodents.

While epidemiological data support the link between reduced heart rate variability (HRV) and a multitude of pathologies, the mechanisms underlying changes in HRV and disease progression are poorly understood. Even though we have numerous rodent models of disease for mechanistic studies, not being able to reliably measure HRV in conscious, freely moving rodents has hindered our ability to extrapolate the role of HRV in the progression from normal physiology to pathology. The sheer number of heart beats per day (>800,000 in mice) makes data exclusion both time consuming and daunting. We sought to evaluate an RR interval exclusion method based on percent (%) change of adjacent RR intervals. Two approaches were evaluated: % change from "either" and "both" adjacent RR intervals. The data exclusion method based on standard deviation (SD) was also evaluated for comparison. Receiver operating characteristic (ROC) curves were generated to determine the performance of each method. Results showed that exclusion based on % change from "either" adjacent RR intervals was the most accurate method in identifying normal and abnormal RR intervals, with an overall accuracy of 0.92-0.99. As the exclusion value increased (% change or SD), the sensitivity (correctly including normal RR intervals) increased exponentially while the specificity (correctly rejecting abnormal RR intervals) decreased linearly. Compared to the SD method, the "either" approach had a steeper rise in sensitivity and a more gradual decrease in specificity. The intersection of sensitivity and specificity where the exclusion criterion had the same accuracy in identifying normal and abnormal RR intervals was 10-20% change for the "either" approach and ∼ 1 SD for the SD-based exclusion method. Graphically (tachogram and Lorenz plot), 20% change from either adjacent RR interval resembled the data after manual exclusion. Finally, overall (SDNN) and short-term (rMSSD) indices of HRV generated using 20% change from "either" adjacent RR intervals as the exclusion criterion were closer to the manual exclusion method with lower subject-to-subject variability than those generated using the 2 SD exclusion criterion. Thus, 20% change from "either" adjacent RR intervals is a good criterion for data exclusion for reliable 24-h time domain HRV analysis in rodents.

[Extraction and recognition of attractors in three-dimensional Lorenz plot].

Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as X, Y and Z axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency ( A PF ) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, A PF was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.

Geometric patterns of time-delay plots from different cardiac rhythms and arrhythmias using short-term EKG signals.

OBJECTIVE: To date, no systematic work has been intended to describe spatio-temporal patterns of cardiac rhythms using only short series of RR intervals, to facilitate visual or computerized-aided identification of EKG motifs for use in clinical practice. The aim of this study was to detect and classify eye-catching geometric patterns of Poincaré time-delay plots from different types of cardiac rhythms and arrhythmias using short-term EKG signals. METHODS: Approximately 150-300 representative, consecutive beats were retrieved from 24-h Holter registers of 100 patients with different heart rhythms. Two-dimensional Poincaré charts were created, and the resulting geometric patterns were transformed into representative familiar eye-catching drawings to interpret different arrhythmias. RESULTS: Poincaré plot representation of RR interval data revealed a wide variety of visual patterns: (i) comet-shaped for sinus rhythm; (ii) torpedo-shaped for sinus bradycardia; (iii) cigarette-shaped for sinus tachycardia; (iv) butterfly-shaped for sinus tachycardia and isolated atrial premature complexes; (v) arrow-shaped for isolated premature complexes and inappropriate sinus tachycardia; (vi) inverted fan-shaped for sinus rhythm with frequent atrial premature complexes; (vii) tornado-shaped for atrial flutter and atrial tachycardia; and (viii) fan-shaped for atrial fibrillation. CONCLUSIONS: Modified Poincaré plots with smoothed lines connecting successive points could accurately classify different types of arrhythmias based on short RR interval sequence variability. Characteristic emergent patterns can be visually identified and eventually could be distinguished by an automatic classification system able to discern between arrhythmias. This work provides an alternative method to interpret time-delay plots obtained from short-term EKG signal recordings.

Poincaré plots as a measure of heart rate variability in healthy dogs.

INTRODUCTION: Poincaré plots remain largely unused for heart rate variability (HRV) analysis in dogs. The aims of this study were to describe, qualitatively and quantitatively, Poincaré plots in healthy dogs, to compare them with other methods of HRV analysis, to assess their day-to-day variability and to investigate the effect of activity on the plots. ANIMALS: Twenty-five healthy dogs. METHODS: Poincaré plots, their standard descriptors, and other measures of HRV were generated from 24-hour ambulatory electrocardiographic recordings and 6 hours of rest and activity. RESULTS: The 24-hour Poincaré plot demonstrated a 'Y' pattern. The arms of the 'Y' were derived mostly from periods of rest and activity populated the stalk. The quantitative descriptors of the plot had strong correlations in the time-domain, with weaker correlations in the frequency-domain. Individuals showed low day-to-day variability of the plot pattern and of the standard deviation of points along the major axis of the plot (SD2), which measures overall HRV. Day-to-day variability was higher for the standard deviation of points perpendicular to the major axis of the plot (SD1), which is a measure of short-term HRV, and for the SD1/SD2 ratio. CONCLUSIONS: Twenty-four-hour Poincaré plots in healthy dogs show a 'Y' pattern with subtle variations unique to the individual. The amount of activity and rest within the recording has a significant effect on the plot. Quantitative analysis of the plot can be used as a surrogate for time-domain analysis of HRV but visual analysis of the pattern provides additional information.

Extraction and recognition of attractors in three-dimensional Lorenz plot / 生物医学工程学杂志

Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as , and axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency ( ) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.

Epileptic Patients are at Risk of Cardiac Arrhythmias: A Novel Approach using QT-nomogram, Tachogram, and Cardiac Restitution Plots.

BACKGROUND: Sudden death is reported in patients who had a history of epilepsy and some authors believed that is due to cardiac arrhythmias. OBJECTIVES: This study aimed to predict that the epileptic patients are at risk of serious cardiac arrhythmias by QT-nomogram, tachogram (Lorenz), and cardiac restitution plots. METHODS: A total number of 71 healthy subjects (Group I) and 64 newly diagnosed epileptic patients (Group II) were recruited from Al-Yarmouk and Baghdad Teaching hospitals in Baghdad from March 2015 to July 2015 and included in this study. The diagnosis of epilepsy achieved clinically, electroencephalograph record and radio-images including computerized tomography and magnetic image resonance. At the time of entry into the study, an electrocardiography (ECG) was done, and the determinants of each ECG record were calculated. The QT-nomogram, tachogram, and cardiac restitution plots were used to identify the patients at risk of cardiac arrhythmias. RESULTS: Significant prolonged corrected QT corrected (QTc) and JT corrected intervals were observed in female compared with male at age ≥50 years while the TQ interval was significantly prolonged in males of Group II. Eight patients of Group II had a significant pathological prolonged QTc interval compared with undetectable finding in Group I. QT nomogram did not disclose significant findings while the plots of Lorenz and restitution steepness disclose that the patients of Group II were vulnerable to cardiac arrhythmias. Abnormal ECG findings were observed in the age extremities (≤18 years and ≥50 years) in Group II compared with Group I. CONCLUSION: Utilization of QT-nomogram, restitution steepness, and tachogram plots is useful tools for detection subclinical vulnerable epileptic patient with cardiac arrhythmias.

Detection of epileptic seizures with a modified heart rate variability algorithm based on Lorenz plot.

PURPOSE: In order to assess whether focal epileptic seizures can be detected and distinguished from exercise we evaluated four different heart rate variability (HRV) methods with short term moving window analysis of 30, 50 or 100 R-R intervals or seconds per analyzed window. METHODS: The four methods consisted of: (1) reciprocal high frequency power based on Fast Fourier Transformation, (2) Cardiac Sympathetic Index (CSI), (3) Modified CSI both based on Lorenz plot, and (4) heart rate differential method. Seventeen patients (12 males, 5 females; age 20-55) had 47 seizures (including three secondary generalized tonic-clonic (sGTC)), which were analyzed during their long term video-EEG monitoring of 1-5 days duration. Positive seizure detection was regarded, when the HRV-value during seizures (1min before to 3min after seizure-onset) exceeded 105% of the highest value during exercise and non-seizure sample-periods of the same patient. RESULTS: Modified CSI100 was the most accurate method: it detected all seizures for 13 of the 17 patients within 6s before till 50s after seizure onset time, even though exercise maximum HR of each patient exceeded that of the seizures. The three sGTC seizures were all detected more than half a minute before the tonic-clonic phase. CONCLUSION: The results indicate a detectable, sudden and inordinate shift toward sympathetic overdrive in the sympathovagal balance of the autonomic nervous system around seizure-onset time, for most patients. The Modified CSI is a promising parameter for a portable ECG-based epilepsy alarm, detecting both focal and sGTC seizures.

Analysis of RR-Lorenz Plot in Patients of Sinus Rhythm With Long RR Interval / 中国循环杂志

Objective: To explore the advantage of RR-Lorenz plot (RR-LP) in analyzing the patients of sinus rhythm with long RR interval. Methods: A total of 308 RR-LP patients with long RR interval were retrospectively studied. The patients were divided into 7 groups according to the type of long RR intervals. ① Sinus bradycardia with arrhythmia group, n=63,②Repeated transient sinus arrest group, n=16, ③Ⅱ° sino-atrial block group, n=14, ④Ⅱ° atrial ventricular block (Ⅱ° AVB) group, n=47, ⑤ Un-passed atrial premature beats (APB) group, n=28, ⑥ Atrial premature beats group, n=72 and ⑦ Premature ventricular beats group, n=68. We analyzed the patients of RR interval greater than 1500 ms with ambulatory electrocardiogram record. Results: ①RR-LP of sinus bradycardia with arrhythmia group showed a single distributing area with 1500 ms for the origin of transverse and longitudinal axis with B line slope at 1, tilt angle of 45°.②RR-LP of repeated transient sinus arrest,Ⅱ° sino-atrial block,Ⅱ° AVB and APB groups showed special four distributing areas with B line slope at (0.51 ± 0.01), tilt angle of (23.04 ± 0.50) °, B line slope at 0.6, tilt angle of (27°), B line slope at (0.57 ± 0.21), tilt angle of (25.69 ± 9.59)° and B line slope at (0.50 ± 0.01), tilt angle of (22.59 ± 0.54) ° respectively.③RR-LP of premature beats groups showed special four regional distributing areas, B line slope for atrial premature beats was at (0.38 ± 0.12), tilt angle of (17.06 ± 5.22) ° and B line slope for ventricular premature beats was at (0.07 ± 0.05), tilt angle of (3.02 ± 2.39) °. Conclusion: RR-LP in patients of sinus rhythm with long RR interval had speciifc morphology and distribution features, the local abnormality could be found in a plane via all RR intervals which provided a differential diagnosis for repeated occurrence of short RR interval.