Biomedical subjects

Birgit Frank

Publications and source records attributed to Birgit Frank.

4 recordsLinked to original sources

PubMed2006

Autonomic information flow improves prognostic impact of task force HRV monitoring.

Heart rate variability (HRV) represents the cardiovascular control mediated by the autonomic nervous system and other mechanisms. In the established task force HRV monitoring different cardiovascular control mechanisms can approximately be identified at typical frequencies of heart rate oscillations by power spectral analysis. HRV measures assessing complex and fractal behavior partly improved clinical risk stratification. However, their relationship to (patho-)physiology is not sufficiently explored. Objective of the present work is the introduction of complexity measures of different physiologically relevant time scales. This is achieved by a new concept of the autonomic information flow (AIF) analysis which was designed according to task force HRV. First applications show that different time scales of AIF improve the risk stratification of patients with multiple organ dysfunction syndrome and cardiac arrest patients in comparison to standard HRV. Each group's significant time scales correspond to their respective pathomechanisms.

Adult↗

PubMed2006

Analysis of complex physiological systems by information flow: a time scale-specific complexity assessment.

In the last two decades conventional linear methods for biosignal analysis have been substantially extended by non-stationary, non-linear, and complexity approaches. So far, complexity is usually assessed with regard to one single time scale, disregarding complex physiology organised on different time scales. This shortcoming was overcome and medically evaluated by information flow functions developed in our research group in collaboration with several theoretical, experimental, and clinical partners. In the present work, the information flow is introduced and typical information flow characteristics are demonstrated. The prognostic value of autonomic information flow (AIF), which reflects communication in the cardiovascular system, was shown in patients with multiple organ dysfunction syndrome and in patients with heart failure. Gait information flow (GIF), which reflects communication in the motor control system during walking, was introduced to discriminate between controls and elderly patients suffering from low back pain. The applications presented for the theoretically based approach of information flow confirm its value for the identification of complex physiological systems. The medical relevance has to be confirmed by comprehensive clinical studies. These information flow measures substantially extend the established linear and complexity measures in biosignal analysis.

Adult↗

PubMed2006

Complex autonomic dysfunction in cardiovascular, intensive care, and schizophrenic patients assessed by autonomic information flow.

BACKGROUND: The cardiovascular control system is mediated by mechanisms acting at different time scales, such as heart period, vagal, sympathetic, and other slower controllers. Since these elements are interrelated in a complex manner, classical control theory fails and information-based description, based on autonomic information flow (AIF) functions, is appropriate. We investigated the hypothesis that AIF functions of typical time scales specifically characterize autonomic dysfunction and prognosis. MATERIALS AND METHODS: Holter recordings of patients with multiple organ dysfunction syndrome (MODS) (26 survivors, 10 non-survivors), heart failure (13 low risk, 13 high risk of cardiac arrest), idiopathic dilated cardiomyopathy (IDC) (26 low risk, 11 high risk), after abdominal aorta surgery (AAS) [32 with length of stay in hospital (LOS) >7 days; 62 with LOS < or =7 days] or with schizophrenia (n=20) were assessed and compared to 20 control subjects. RESULTS: We found different AIF time scales discriminating risk. AIF measures of heart beat period had predominant prognostic value in heart failure patients, those of vagal communication in MODS and IDC, and those of long-term communication after AAS. Schizophrenic patients were discriminated from controls by vagally mediated communication. CONCLUSION: Different time scales of AIF represent specific pathophysiological aspects of altered complex autonomic control (communication) and consequently have predictive implications.

Autonomic Nervous System↗

PubMed2006

Complexity of heart rate fluctuations in near-term sheep and human fetuses during sleep.

We investigated how the complexity of fetal heart rate fluctuations (fHRF) is related to the sleep states in sheep and human fetuses. The complexity as a function of time scale for fetal heart rate data for 7 sheep and 27 human fetuses was estimated in rapid eye movement (REM) and non-REM sleep by means of permutation entropy and the associated Kullback-Leibler entropy. We found that in humans, fHRF complexity is higher in non-REM than REM sleep, whereas in sheep this relationship is reversed. To show this relation, choice of the appropriate time scale is crucial. In sheep fetuses, we found differences in the complexity of fHRF between REM and non-REM sleep only for larger time scales (above 2.5 s), whereas in human fetuses the complexity was clearly different between REM and non-REM sleep over the whole range of time scales. This may be due to inherent time scales of complexity, which reflect species-specific functions of the autonomic nervous system. Such differences have to be considered when animal data are translated to the human situation.

Algorithms↗