Background The canine cardiac system has been the model against which many Class III cardiac devices are validated. Thus, it is expected that the canine heart has very similar electrical model to that found in humans. In 1999, the absence of Heart Rate Turbulence (HRT) after a single Pre-Ventricular Contraction (PVC) was linked to high-risk patient after acute myocardial infarction. Studies of HRT were performed on high-risk patients with Holter-Monitors as were most subsequent HRT studies. If HRT could potentially be used as a risk factor of heart disease, it is interesting to study whether HRT is present following a PVC in otherwise healthy canines. Methods For multiple months, five non-medicated, healthy canines were chronically monitored from between 1 and 8 sessions each. At each session, the canines were ventricularly paced to induce PVCs. Electrical signals, as seen through both a right-ventricular lead and Electrocardiogram (ECG) signals, were captured and analyzed to determine whether the canines displayed HRT following each induced PVC. As a contrasting data set, for the majority of the canines, data was also collected once the canines were sedated. Results HRT was noted in all non-medicated and healthy canines. Of the two factors of HRT (slope and onset), TS was the most prominent indicator of HRT. In each canine, the slope was far greater than the 2.5 ms per RR interval threshold varying from 9.8 to 68.8 ms per RR interval. The onset was marked as HRT (onset less than 0%) in 22 of the 26 session. Additional data was analyzed for healthy yet medicated canines showed that sedation affected HRT, but that HRT was generally noted. Conclusion The canine model displayed a similar HRT characteristic as humans during normal and parasympathetic inhibited states. The presence of HRT in canines is most reliable when using TS. Further study in this area with naturally occurring PVCs would be of interest.

Abstract Heart rate variability (HRV) is used in the assessment of cardiovascular health. However, often contradictory results have impeded the efficient use of HRV in clinical practice. HRV signals can contain artifacts leading to errors in the interpretation of HRV results. Various methods have been used for artifact editing, but there is relatively little information on how the actual editing can influence the HRV measures. The main aim of this thesis was to improve the reliability of HRV analysis by concentrating on the HRV signal preprocessing methods. The effects of three editing methods on the HRV of short (512 R-R) and long-term (24-hour) R-R interval data were studied with non-edited and edited data from healthy subjects (n=10) and patients with acute myocardial infarction (AMI) (n=10). The effects of ectopic beats on short (α1) and long-term (α2) fractal scaling exponents were studied by inserting artificial ectopic beats into the HRV signals of 20 healthy subjects and 20 AMI patients. The prognostic significance of edited and non-edited α1 and α2 was studied in random elderly (n=84) and post-AMI (n=84) populations. A new method to quantify respiratory sinus arrhythmia (RSA) was developed based on the HRV signals of 13 healthy subjects. A new measure, the RSA index, was defined to evaluate the risk to sudden cardiac death (SCD) in 1631 AMI patients. Lastly, a new algorithm was developed in order to edit heart rate (HR) turbulence occurring immediately after a ventricular premature beat (VPB). The effects of HR turbulence editing on the HRV analysis were studied in 267 AMI patients. Editing had distinct effects on the HRV analysis depending on the editing method and data type. Deletion editing was found to be unsuitable for the HRV spectrum analysis. There was no universal editing method for the time and frequency domain HRV analyses. Unedited ectopic beats increased the randomness of short-term R-R interval dynamics, especially in AMI patients. However, unedited α1 differed significantly between survivors and those who died during the follow-up. Ectopic beats do not necessarily need to be edited if fractal analysis is used in the risk evaluation. A depressed RSA index was found to be a strong predictor of SCD but a weak predictor of non-SCD in AMI patients. Editing of HR turbulence affected differently the various HRV measures. ULF and VLF components were most clearly influenced by HR turbulence removal. The amount of VBPs had an important impact on the results. When the VBPs/hour were >50, ULF and VLF were >30% lower after turbulence removal. The results of this thesis highlight the importance of editing the erroneous or irrelevant R-R interval oscillation in an HRV analysis. The careful choice of preprocessing method is essential if one wishes to obtain reliable HRV analyses for clinical purposes.

No description available.

No description available.