Hearte Rate Variability

An Electrocardiogram (ECG) is defined as a test that is performed on the heart to detect any abnormalities in the cardiac cycle. Automatic classification of ECG has evolved as an emerging tool in medical diagnosis for effective treatments. The work proposed in this paper has been implemented using MATLAB. In this paper, we have proposed an efficient method to classify the ECG into normal and abnormal as well as classify the various abnormalities. To brief it, after the collection and filtering the ECG signal, morphological and dynamic features from the signal were obtained which was followed by two step classification method based on the traits and characteristic evaluation. ECG signals in this work are collected from MIT-BIH, AHA, ESC, UCI databases. In addition to this, this paper also provides a comparative study of various methods proposed via different techniques. The proposed technique used helped us process, analyze and classify the ECG signals with an accuracy of 97% and with good convenience.

Background: Essential hypertension (EH) is traditionally associated with overactivity of sympathetic and renin-angiotensin systems and has multifactorial origin, arising from an interaction between susceptibility genes and environmental factors.

Objectives: to examine the autonomic nervous system, polymorphism of the angiotensin-converting enzyme (ACE) and β2-adrenergic receptor (β2-AR) genes in hypertensive patients with complications (left ventricular hypertrophy and ischemic stroke).

Methods: Heart rate variability (HRV) with active tilt-test, 24 h blood pressure monitoring (BP), echocardiography, Gln27Glu polymorphism of β2-AR, and I/D polymorphism of ACE genes were studied in 250 Kyrgyz EH patients with and without complications.

Results: A significant reduction of HRV and decreased response of LF (low frequency) component to tilt-test in hypertensive patients were observed compared to control. Tilt-test in patients with complications of EH had shown inverse response of LF to orthostatic test. Patients with Gln27Gln genotype in comparison to other variants of Gln27Glu polymorphism of β2-AR were characterized by increasing meanings of BP and its morning raises, which possibly may cause increasing of left ventricular mass in these patients. In EH patients with ischemic stroke, DD genotype frequency was more than twofold greater than those with uncomplicated EH. Night hypertension, greater BP variability, and increased carotid intimal thickness are common features in patients with the DD genotype of the ACE gene.

Conclusion: The inverse reaction of LF to orthostatic test can be regarded as an unfavorable prognostic sign, predisposing complications of EH. Our data support an association between I/D polymorphism of ACE gene and stroke in patients with EH.

PURPOSE: The autonomic maneuvers are simple methods to evaluate autonomic balance, but the association between autonomic maneuvers and heart rate variability (HRV) in hemodialysis patients remains unknown. This study aimed to evaluate the correlation between HRV and respiratory sinus arrhythmia (RSA) and Valsalva maneuver (VM) indexes in hemodialysis patients and to compare two methods for RSA indexes acquisitions.
METHODS: Forty-eight volunteers on hemodialysis (66.7 % men) were evaluated by VM, RSA, and 24 h Holter monitoring. At the VM, the Valsalva index (VI) was the variable considered. In the RSA, the ratio and difference between the RR intervals of inspiratory and expiratory phase (E:I and E-I, respectively) were considered by traditional form (average of respiratory cycles) and independent respiratory cycles (E:Iindep and E-Iindep). The HRV indexes evaluated were standard deviation of all normal RR intervals (SDNN), standard deviation of sequential 5-min RR interval means (SDANN), root mean square of the successive differences (rMSSD) and percentage of adjacent RR intervals with difference of duration greater than 50 ms (pNN50).
RESULTS: The SDNN, SDANN showed significant correlation with all classic indexes of RSA (E:I: r = 0.62, 0.55, respectively, E-I: r = 0.64, 0.57, respectively), E:Iindep (r = 0.59, 0.54, respectively), E-Iindep (r = 0.47, 0.43, respectively) and VI (r = 0.42, 0.34, respectively). Significant correlation of rMSSD with E:I (r = 0.37), E-I (r = 0.41) and E:Iindep (r = 0.34) was also observed. There was no association of any variable with pNN50. Have been show high values for all variables of independent cycles method (p < 0.05).
CONCLUSION: The autonomic maneuvers, especially RSA, are useful methods to evaluate cardiac autonomic function in hemodialysis patients. The acquisition of the RSA index by independent cycles should not be used in this population.