ANALYSIS OF HEART RATE VARIABILITY FROM24-HOUR AMBULATORY ELECTROCARDIOGRAPHIC RECORDINGS, ACTA UNIVERSITATIS OULUENSIS D Medica 1087

Heart rate variability (HRV) is used in the assessment of cardiovascular health. However, oftencontradictory results have impeded the efficient use of HRV in clinical practice. HRV signals cancontain artifacts leading to errors in the interpretation of HRV results. Various methods have beenused for artifact editing, but there is relatively little information on how the actual editing caninfluence the HRV measures. The main aim of this thesis was to improve the reliability of HRVanalysis by concentrating on the HRV signal preprocessing methods.\nThe 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) andpatients with acute myocardial infarction (AMI) (n=10). The effects of ectopic beats on short (á1)and long-term (á2) fractal scaling exponents were studied by inserting artificial ectopic beats intothe HRV signals of 20 healthy subjects and 20 AMI patients. The prognostic significance of editedand non-edited á1 and á2 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 HRVsignals of 13 healthy subjects. A new measure, the RSA index, was defined to evaluate the risk tosudden cardiac death (SCD) in 1631 AMI patients. Lastly, a new algorithm was developed in orderto 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. \nEditing had distinct effects on the HRV analysis depending on the editing method and datatype. Deletion editing was found to be unsuitable for the HRV spectrum analysis. There was nouniversal editing method for the time and frequency domain HRV analyses. Unedited ectopicbeats increased the randomness of short-term R-R interval dynamics, especially in AMI patients.However, unedited á1 differed significantly between survivors and those who died during thefollow-up. Ectopic beats do not necessarily need to be edited if fractal analysis is used in the riskevaluation. A depressed RSA index was found to be a strong predictor of SCD but a weakpredictor of non-SCD in AMI patients. Editing of HR turbulence affected differently the variousHRV measures. ULF and VLF components were most clearly influenced by HR turbulenceremoval. 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. \nThe results of this thesis highlight the importance of editing the erroneous or irrelevant R-Rinterval oscillation in an HRV analysis. The careful choice of preprocessing method is essential ifone wishes to obtain reliable HRV analyses for clinical purposes.

ISBN-10:
978-951-42-9348-1
Kieli:
eng.
Sivumäärä:
178 s.
Tekijät:
PELTOLA MIRJA
Tuotekoodi 014057
20,00 €