Aging and the complexity of cardiovascular dynamics

Abstract

Biomedical signals often vary in a complex and irregular manner. Analysis of variability in such signals generally does not address directly their complexity, and so may miss potentially useful information. We analyze the complexity of heart rate and beat-to-beat blood pressure using two methods motivated by nonlinear dynamics (chaos theory). A comparison of a group of healthy elderly subjects with healthy young adults indicates that the complexity of cardiovascular dynamics is reduced with aging. This suggests that complexity of variability may be a useful physiological marker.

Predicting survival in critical patients by use of body temperature regularity measurement based on approximate entropy

“…As r is normalized by the standard deviation, ApEn is amplitude scale independent. These values have proven to perform well in many cases (Abásolo et al, 2005;Pincus and Keefe, 1992;Kaplan et al, 1991). Results for each register and each class are shown in Table 1.…”

“…In this paper we estimated the regularity of the body temperature register using approximate entropy (ApEn) averaged along overlapping epochs of the registers (Pincus, 1991). Previous studies have demonstrated there are clinical implications of body temperature curve complexity (Varela et al, 2005(Varela et al, , 2003 and ApEn has been successfully used to estimate the regularity of other biomedical signals (Pincus and Keefe, 1992;Kaplan et al, 1991). ApEn changes have often been seen to be predictive of subsequent clinical changes.…”

Electrophysiological entropy in younger adults, older controls and older cognitively declined adults

“…Notably, some of the studies that have compared healthy younger and older adults have used cardiovascular data and not EEG data (e.g., Kaplan et al, 1991). Furthermore, as noted in the introduction, while research and theory suggests that measures of electrophysiological signal complexity and entropy might be useful markers of age-and disease-related cognitive decline, the majority of the studies have compared Alzheimer's Disease patients with healthy age-matched controls Escudero et al, 2006;Sneddon et al, 2005).…”

“…Some theoretical models suggest that generic properties of brain function, for example, the level of intra-network variability, may be causally related to the patterns of age-and diseaserelated cognitive decline (Li and Lindenberger, 1998;Li et al, 2006). The idea that entropy may be of general functional significance comes from studies that have found reduced uncertainty associated with a variety of age-related chronic conditions Kaplan et al, 1991;Lipsitz, 2002). Entropy measures may help to characterise vulnerability in ageing in a way that conventional approaches which require a stimulus or task and the measurement of some contrast be it using fMRI, EEG or MEG, are unable to assess.…”

“…An emerging body of research now suggests that measures of bio-signal complexity and entropy might be useful markers of age-and disease-related cognitive decline. Some re-searchers have argued that there is a general loss of complexity with ageing and disease Kaplan et al, 1991;Lipsitz, 2002). As a result, the response of these systems is postulated to be less adaptive.…”