Short-term Heart Rate Variability Analysis in Healthy Dogs of Different Ages

Background: The modulation of heart rate by autonomic nervous system may be evaluated by the heart rate variability (HRV), which illustrates the fluctuations between RR intervals. To evaluate this analysis, the intervals between 2 QRS complexes are measured. In general, high HRV values are expected in healthy individuals; otherwise, low values are indicative of organism dysfunction. Studies conducted in healthy humans show that HRV suffers reduction with ageing and that there is autonomic immaturity in neonates. The aim of this study was to describe the characteristic pattern of cardiac autonomic behavior in healthy dogs in different age groups through short-term HRV analysis.Materials, Methods & Results: A total of 87 healthy dogs were studied. HRV was analyzed in time and frequency domain, using Holter and heart rate monitor. It was observed that puppies (below one year old) presented a lower parasympathetic predominance and, consequently, lower HRV values on time domain (SDNN, PNN50% e RMSSD) compared to the other 2 groups and on frequency domain (LF, HF and LF/HF) compared to the adult animals group (between 1 and 7-year-old), which presented higher HRV values when compared to the other groups. Elderly dogs (over 8-year-old) exhibited a natural tendency to decrease cardiac parasympathetic HRV indexes.Discussion: The use of the HRV method as a prognostic index and as an arrhythmogenic marker for various canine heart diseases presents interesting perspectives. However, before it may be employed for these purposes, a better understanding should be established regarding the physiological behavior of autonomic cardiac modulation in different age groups to serve as a basis for future analyses. This study observed that puppies presented higher values for HR and, therefore, shorter RR intervals than the other groups (adult and elderly dogs), what was observed on Holter and heart rate monitor methods (HRM). There were significant differences between puppies and the other 2 groups (adults and elderly) for all time-domain variables using both methods (Holter and HRM methods). SDNN was significantly lower in puppies compared to adults and elderly dogs. In addition, both RMSSD and PNN50%, which were more reliable over shorter periods of time, also presented means and medians that were significantly lower in puppies. Regarding frequency-domain HRV parameters observed on Holter method, these indexes were decreased on the elderly group compared to adult dogs, which is a possible effect of aging. Also, puppies revealed lower frequency-domain HRV parameters on both methods when compared to adult dogs. The influence of age on HRV is possibly related to the stage of development of an individual, starting at conception up to the maturity in relation to the mechanisms that cause variations in HR. There are studies in humans that suggest a gradual increase in parasympathetic activity during childhood, followed by a steady decrease as aging occur. The present study observed the same pattern in dogs. The balance between sympathetic and parasympathetic systems is influenced by age in dogs, which alters HRV values in the short-term. The HRV method´s analysis is relatively simple and non-invasive for assessing cardiac autonomic function; also, it is widely used in human medicine as a risk measure for sudden cardiac death. The 24-hour HRV analysis is highly challenging, as it is time-consuming, expensive, delays diagnosis, and has a large number of artifacts; in this way, standards for its short-term analysis were developed. Keywords: cardiology, autonomic nervous system, heart rate monitor, Holter.

Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11340 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (bias 0.20 ms, p < 0.001) and nocturnal recordings (bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

A novel single-lead handheld atrial fibrillation detection system

Objective: The single-lead handheld atrial fibrillation (AF) detection device is suitable for daily monitoring or early screening of AF in the hospital. However, the signal quality and the reliability of AF detection algorithm still need to be improved. This study proposed a novel AF detection system with a user-friendly interaction and a lightweight and accurate AF detection algorithm. Approach: The system consisted of a single-lead handheld electrocardiogram (ECG) device with a novel appearance like a gaming handle and a smartphone terminal embedded with AF detection. After feature optimization, the rule-based multi-feature AF detection algorithm had relatively good AF detection ability. Three types of experiments were designed to test the performance of the system. 1) Test the accuracy and time/memory cost of the AF detection algorithm. 2) Compare the proposed device with the standard device Shimmer. 3) Use the simulator to test the effectiveness of the system. Main results: The percentage of differences of successive RR intervals larger than 50 ms (PNN50), minimum value of RR intervals (minRR), and coefficient of sample entropy (COSEn) were features chosen for AF detection. 1) The sensitivity, specificity, and accuracy were 96.00%, 99.75%, 97.88% on the MIT-BIH AF database, and 98.50%, 94.50%, 96.50% on the clinical database we founded. The time/memory cost of the proposed algorithm was much smaller than that of Support Vector Machine (SVM). 2) The mean correlation coefficient of RR was 0.9950, indicating a high degree of consistency. 3) This system showed the effectiveness of AF detection. Significance: The proposed single-lead handheld AF detection system is demonstrated to be accurate, lightweight, consistent with the standard device, and efficient for AF detection.

Cardiovascular Autonomic Function Tests in Patients of Obsessive–Compulsive Disorder: A Cross-Sectional Study

Background: Patients with psychiatric disorders are at an increased risk of developing cardiovascular disease, reducing life expectancy. Autonomic dysfunction has been linked to this increased risk; many studies have found reductions in heart rate variability (HRV). Only a few studies have systematically explored the relationship between obsessive–compulsive disorder (OCD) and autonomic function, and they have found contradicting results. The present study is intended to explore comprehensive autonomic functions in OCD patients and compare them with healthy controls. Methods: A total of 18 OCD patients meeting Diagnostic and Statistical Manual of Mental Disorders - 5 (DSM-5) criteria were enrolled to undergo comprehensive autonomic function testing, and the results were compared with 25 age- and sex-matched healthy controls. Results: Time-domain parameters of HRV such as standard deviation of the RR intervals, coefficient of variance of RR intervals, standard deviation of differences between adjacent RR intervals, root square of the mean of the sum of the squares of differences between adjacent RR intervals, and percentage of number of RR interval differences ≥ 50 ms were significantly lower in OCD patients, indicating lesser parasympathetic tone. Frequency-domain parameters such as total power and very low frequency were significantly lower in OCD patients, indicating a significant decrease in autonomic tone. Nonlinear parameters such as dispersion of points perpendicular to the line of identity and dispersion of points along the line of identity were significantly lower in OCD patients, indicating altered vagal and sympathetic tone. In autonomic reactivity tests, the fall in systolic blood pressure during the lying to standing test and change in diastolic blood pressure during the cold pressor test were significantly altered in OCD patients, indicating abnormal sympathetic reactivity. There was no significant correlation between autonomic parameters and the severity of OCD. Conclusion: OCD is characterized by a decreased parasympathetic tone and abnormal sympathetic reactivity compared to normal controls.

Effects of 12-week Pilates training program on cardiac autonomic modulation: a randomized controlled clinical trial

Aim: To evaluate the effects of 12-week Pilates training program on cardiac autonomic modulation. Materials & methods: A randomized controlled trial of a 12-week Pilates training program was conducted. A total of 54 men were randomly allocated to either a control or a Pilates group. Initially, the RR intervals were captured for 20 min for later analysis of heart rate variability (HRV). The training protocol was then initiated, in which the Pilates group performed 36 sessions of the Pilates method for approximately 60 min each session, three-times a week, totaling 12 weeks. The control group was instructed to maintain their normal activities during this period. One week after the end of the training, the final evaluations were performed with the capture of RR intervals in both the groups. Linear indices in the time (SDNN and rMSSD) and frequency (low frequency [LF] and high frequency [HF]) domains, and the Poincaré plot (SD1 and SD2) were used. Nonlinear indices were also analyzed (approximate entropy and detrended fluctuation analysis). Descriptive statistics and generalized mixed models were performed. Results: There was a group effect for LF (ms2) and a time effect for SD2. There was a training effect observed by the time*group interactions in which an increase in global HRV indices was found for the Pilates group after 12 weeks (SDNN: mean difference [MD] = 9.82; standard deviation [SD] = 18.52; ES = -0.514; LF [ms2]: MD = 334.23; SD = 669.43; ES = -0.547; SD2: MD = 14.58; SD = 24.28; ES = -0.693). Conclusion: A 12-week Pilates training program promotes significant improvement in global modulation of HRV in the Pilates group considering the significant increase in SDNN, LF (ms2) and SD2 indices. Trial registration number: NCT03232866 .

Analysis of frequency ranges of heart rate variability and estimation errors of respiratory sinus arrhythmia in aging

The clinical significance of heart rate variability (HRV) was assessed at the end of the last century, despite the fact that HRV studies have been conducted since the mid-19th century. In recent years, HRV has been increasingly used for non-invasive monitoring of the autonomic nervous system. However, the interpretation of HRV features is still not fully understood and widely discussed. It is known that HRV fluctuations are created by various regulatory systems of the body, which have different natural frequencies. The estimated HRV parameters are SDNN and RMSSD indicators – standard deviations of a number of RR-intervals and a number of first differences of RR-intervals, respectively. The purpose of the article was to calculate the power decrease with aging in different frequency ranges, analyze the errors of spectral estimates, and compare the spectral estimates of RSA with the values of RMSSD indicators. Simultaneous ECG and respiration records from the Fantasia Physio Bank database were used as initial data. For reference estimates, the powers in the range of respiration rate found from the records of respiration measurements are taken. It is shown that with age the power of the HF range decreases most rapidly, and the VLF range decreases most slowly. HF oscillation amplitudes are compared with RMSSD values. It is proposed to consider the RMSSD indicator as an assessment of the speed parameter of the regulatory system. Spectral methods are used to estimate the power of individual frequency ranges. For non-invasive monitoring of the autonomic nervous system, spectral estimates of the power of the LF and HF ranges are used. With aging, stress, and various diseases, the activity of regulatory systems decreases, but it remains unclear in which regulatory systems and to what extent violations occur.

Alternations in the cardiovascular autonomic regulation and growth factors in autism

Autism spectrum disorder (ASD) represents a serious neurodevelopmental disorder associated with autonomic nervous system dysregulation. The aim was to study complex cardiovascular autonomic regulation using heart rate variability (HRV) and systolic blood pressure variability (SBPV) linear/non-linear analysis at rest and during orthostasis, and to assess plasma levels of epidermal growth factor (EGF) and vascular endothelial growth factor (VEGF) in autistic children. Twenty-five ASD boys and 25 age and gender-matched children at the age 7 15 years were examined. After venous blood taking, continuous ECG and blood pressure biosignals were recorded at rest and during orthostasis. Evaluated parameters: RR intervals, high- and low-frequency band of HRV spectral analysis (HF-HRV, LF-HRV), symbolic dynamics parameters 0V %, 1V %, 2LV %, 2UV %, low- and high-frequency band of SBPV (LF-SBPV, HF-SBPV), systolic, diastolic, mean blood pressure, EGF, VEGF plasma levels. RR intervals were significantly shortened and the HF-HRV, LF-SBPV, HF-SBPV parameters were significantly lower at rest, the HF-HRV and LF-SBPV remained lower during orthostasis in autistic children compared to controls (p0.05). EGF plasma levels were significantly lower in ASD compared to controls (p=0.046). No significant differences were found in remaining parameters. Our study revealed tachycardia, cardiovagal underactivity, and blunted sympathetic vasomotor regulation at rest and during orthostasis in autistic children. Additionally, complex heart rate dynamics are similar in autistic children than controls. Furthermore, EGF was reduced in autistic children without significant correlations with any autonomic parameters. We suggest that the abnormal complex cardiovascular reflex control could contribute to understanding the pathway linking autonomic features and autism.

The Sensitivity of The Heart Rate Detection for Atrial Electrograms Signal

Atrial Fibrillation (AF) is the most familiar example of arrhythmia that will occur health problems such as stroke, heart failure and other complications. Globally, the number of AF patients will more than triple by 2050 worldwide. Current methods involve performing large-area ablation without knowing the exact location of key parts. The reliability of the technology can be used as a target for atrial fibrillation’s catheter ablation. The factors that leading to the onset of atrial fibrillation include the triggering factors that induce arrhythmia and the substrate that maintains the arrhythmia. The project’s aim is to create a method for identifying AF that can be used as screening tool in medical practice. The primary goals for the detection method’s design are to develop a MATLAB software program that can compare the complexity of a normal ECG signal and an AF ECG signal. Currently, this can be achieved by the ECG Signal’s R peaks and RR Interval. For AF detection, there are more R peaks and RR Intervals and it is irregular. In this research, the detection of AF is based on the heart rate (RR Intervals). For the ECG preprocessing, Pan-Tompkins Algorithm and Discrete Wavelet Transform is used to detect the sensitivity on the R peaks and RR Intervals. As a result, Discrete Wavelet Transform algorithm gives 100% sensitivity for the dataset obtained from MIT-BIH Atrial Fibrillation and MIT-BIH Arrhythmia Database.