Heart rate variability : linear and nonlinear analysis with applications in human physiology

Cardiovascular diseases are a growing problem in today?s society. The World Health Organization (WHO) reported that these diseases make up about 30% of total global deaths and that heart diseases have no geographic, gender or socioeconomic boundaries. Therefore, detecting cardiac irregularities early-stage and a correct treatment are very important. However, this requires a good physiological understanding of the cardiovascular system. The heart is stimulated electrically by the brain via the autonomic nervous system, where sympathetic and vagal pathways are always interacting and modulating heart rate. Continuous monitoring of the heart activity is obtained by means of an ElectroCardioGram (ECG). Studying the fluctuations of heart beat intervals over time reveals a lot of information and is called heart rate variability (HRV) analysis. A reduction of HRV has been reported in several cardiological and noncardiological diseases. Moreover, HRV also has a prognostic value and is therefore very important in modeling the cardiac risk. The fact that heart rate variability is a result of both linear and nonlinear fluctuations opened new perspectives as previous research was mostly restricted to linear techniques. Some situations or interventions can change the linear content of the variability, while leaving the nonlinear fluctuations intact. Also the reverse can happen: interventions, which up till now have been believed to leave cardiovascular fluctuations intact based on observations with linear methods, can just as well modify the nonlinear fluctuations. This can be important in the development of new drugs or treatments for patients. Therefore, this thesis focuses on the quantification of the nonlinear characteristics in autonomic heart rate regulation. Advanced techniques from nonlinear system dynamics and chaos theory are applied. First, we present a new technique that can discriminate between preterm neonates with and without cardiovascular abnormalities. Further, we show in a healthy population the typical circadian (24h) profiles with several nonlinear HRV parameters as a function of age and gender. A higher nonlinear behaviour is observed during the night while nonlinear heart rate fluctuations decline with age. The changes during the transition phases of waking up and going to sleep are described in detail. In another chapter we identify how HRV can be used to detect stress. Adaptations of the cardiovascular system in astronauts after space missions are also investigated. We prove the change in nonlinear heart rate dynamics, still present after 5 days upon return to earth and more expressed in the day period. After one month, a complete cardiovascular recovery is found. These findings are verified in a head-down bed rest (HDBR) study, simulating microgravity conditions. In addition, we show that Chinese herbal medicine restricts the influences of icrogravity environment during HDBR on the cardiovascular regulation, though only partially functions as a countermeasure. Finally, we reveal that epileptic patients have a higher HR and decreased HRV compared to a normal population. Although vagal nerve stimulation reduces the epileptic activity, it affects cardiac autonomic modulation. The affected autonomic cardiac control in patients with refractory epilepsy might play an important role in arrhythmias and sudden cardiac death. To summarize, we can say that this PhD thesis shows that nonlinear HRV techniques give additional information about autonomic cardiac control in several circumstances which cannot be obtained with standard linear analyses.