Relation in-between autonomic cardiovascular control and central nervous system activity during sleep using spectrum-weighten frequencies

The present study is concerned with relevance of the spectrum-weighted frequencies of both heart rate variability (HRV) and electroencephalogram (EEG). The frequencies represent the balance point of power within a certain spectral range. The predictive value of the frequencies and their mutual interrelations are demonstrated with respect to different sleep stages based on data from a single case. In particular, the revealed stage-dependent relationships between frequencies from HRV and EEG suggest a close interrelation between autonomic cardiovascular control and activity of central nervous system. The results demonstrate that the easy-to-assess frequencies may provide a simple indicator of the sleep quality within the scope of comfortable patient monitorin

A Web Based System for Sleep Disorders Management

This presentation was given at the Med-e-tel 2005 Conference in Luxembourg on April 7th, 2005.Internet as eHealth Tool: A Web-based system enabling population and physicians to learn about sleep disorders, to self-assess their sleep using an expert system including a Multidimensional Scaling algorithm to visualise the results, and to consult a physician via Internet enhancing the efficiency of diagnosis and treatment will be presented.Institute Psychophysiology and Rehabilitation, Vyduno Str. 4, Palanga, Lithuania and Vytautas Magnus University, Lithuani

Prevalence and predictors of sleep apnea in patients with stable coronary artery disease: a cross-sectional study

Audrius Alonderis,1 Giedrius Varoneckas,1 Nijole Raskauskiene,2 Julija Brozaitiene1 1Laboratory of Clinical Physiology and Rehabilitation, Behavioral Medicine Institute, Lithuanian University of Health Sciences, Palanga, Lithuania; 2Laboratory of Psychosomatic Research, Behavioral Medicine Institute, Lithuanian University of Health Sciences, Palanga, Lithuania Background: Sleep apnea (SA) is increasingly recognized as being important in the prognosis of patients with coronary artery disease (CAD); however, symptoms of SA are not easily identified, and as many as 80% of sufferers remain undiagnosed. Aim: This cross-sectional study investigated the prevalence and predictors of SA that may help to increase the awareness and diagnosis of SA in stable CAD patients. Materials and methods: Polysomnography was performed in 772 medically stable CAD patients with untreated SA recruited from the Clinic of Cardiovascular Rehabilitation. Patients were predominantly male (76%), median age was 58 years (32–81). All subjects completed the Epworth sleepiness scale (ESS). The frequency of all apneas and hypopneas associated with 3% oxygen desaturation is referred to as the apnea–hypopnea index (AHI). Mild-to-severe SA was defined as AHI ≥5/h, moderate-to-severe SA as AHI ≥15/h. Results: AHI was within a range of values that was considered normal or only mildly elevated. The median AHI was 3.4 (interquartile range [IQR 1–9]), and 39% of patients had unrecognized mild-to-severe SA (moderate-to-severe in 14%), which was not higher than other known risk indicators for CAD such as hypertension and obesity (83% and 47%, respectively). These patients did not show sleepiness and the risk-related cut-off score for excessive daily sleepiness was lower than the official for ESS. Conclusion: Hypertension, age, male gender, obesity, ESS ≥6, and left ventricular ejection fraction ≤45% were the best predictors of mild-to-severe SA. While, male gender, age 50–70 years and, mainly, the presence of obesity but not hypertension were clinical predictors for moderate-to-severe SA. In addition, association between mild-to-severe SA and obesity was not evident in women. SA is prevalent comorbidity in the stable CAD patients, especially in its asymptomatic mild form. We suggest that SA should be considered in the secondary prevention protocols for CAD. Keywords: apnea–hypopnea index, AHI, age, CAD, gender differences, sleep apnea&nbsp

Correlation in the heart rate data

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed