The cardiovascular system is the major communication and distribution system in higher living organisms. It interacts with other complex systems in the body, such as the nervous system, respiratory system, endocrine system, immune system, renal system, etc. This interaction forms a multitude of inter-coupled sub-systems, operating at various time scales and spatially distributed across the body. These specific sub-systems maintain their homeostatic operation points in optimally performing specific functions. Yet, despite their specific functionality, these sub-systems are not fully separable from one another. The key principle of complex systems is this inseparability, where the total system shows behaviour more complex than the superposition of its sub-components.
The primary synchronicity of the cardiovascular system is that of its pacemaker, the sinoatrial node. The complex dynamics of the entire system modulates this pacemaking action, giving rise to the observable variability of the heart rate. This heart rate variability (HRV) in humans has been shown to display highly non-trivial characteristics of dynamic complexity, markedly different in health and disease.
Thus the cardiovascular system is a complex system in the true sense of the word. Operating at a range of mesoscales, it evades adequate description in terms of low-dimensional dynamics, yet exhibits symmetries reducing dimensionality far below that of a truly statistical system. Indeed, alternative approaches, stemming from both dynamical systems and statistical physics analysis methodologies, have been applied to derive heart rate variability characteristics in health and disease, alas, only with a moderate degree of success.
This is unfortunate, as heart rate and heart rate variability can be readily measured in a non-invasive way and evaluated both offline and in real time, potentially providing vital information about the functioning of the cardiovascular system. As ambient health technology is becoming part of daily life, the capabilities of data-rich, individualised medicine pose unprecedented challenges for information technology. One of the rapidly emerging technologies in ambient health care is pervasive cardiac surveillance.
The availability of hardware solutions for collecting streaming information on the dynamics of heart rate of individuals during daily life may revolutionise health care. This may contribute to an understanding of complex cardiovascular diseases of heterogeneous origin, and also to a deeper understanding of human nature in complex societal tasks, by providing insight into the interdependence of physiological predisposition and individual, psychological and group human social involvement.
We welcome contributions addressing complexity measures of heart rate, as an univariate variable or in an interacting, causally coupled network setting with other variables. Of special, although not exclusive interest for this Research Topic are contributions addressing the role of various measures of entropy in the characterisation of heart rate complexity, and transfer entropy in causal combination with other physiological variables. Indeed, entropy is a binding information theoretic concept, bridging complexity with predictability, making it a measure of choice for the challenging task of capturing the complex dynamics of the cardiac regulatory system in a daily setting and providing measures of risk in cases of regulatory dysfunction.
This Research Topic welcomes all contributions to the state-of-the-art quantitative assessment of the complexity of the heart rate. In particular, with the aim of revealing and characterising the cardiovascular system's complexity, as reflected in HRV, for the prediction and prognosis of the future of the system's dynamics.
The cardiovascular system is the major communication and distribution system in higher living organisms. It interacts with other complex systems in the body, such as the nervous system, respiratory system, endocrine system, immune system, renal system, etc. This interaction forms a multitude of inter-coupled sub-systems, operating at various time scales and spatially distributed across the body. These specific sub-systems maintain their homeostatic operation points in optimally performing specific functions. Yet, despite their specific functionality, these sub-systems are not fully separable from one another. The key principle of complex systems is this inseparability, where the total system shows behaviour more complex than the superposition of its sub-components.
The primary synchronicity of the cardiovascular system is that of its pacemaker, the sinoatrial node. The complex dynamics of the entire system modulates this pacemaking action, giving rise to the observable variability of the heart rate. This heart rate variability (HRV) in humans has been shown to display highly non-trivial characteristics of dynamic complexity, markedly different in health and disease.
Thus the cardiovascular system is a complex system in the true sense of the word. Operating at a range of mesoscales, it evades adequate description in terms of low-dimensional dynamics, yet exhibits symmetries reducing dimensionality far below that of a truly statistical system. Indeed, alternative approaches, stemming from both dynamical systems and statistical physics analysis methodologies, have been applied to derive heart rate variability characteristics in health and disease, alas, only with a moderate degree of success.
This is unfortunate, as heart rate and heart rate variability can be readily measured in a non-invasive way and evaluated both offline and in real time, potentially providing vital information about the functioning of the cardiovascular system. As ambient health technology is becoming part of daily life, the capabilities of data-rich, individualised medicine pose unprecedented challenges for information technology. One of the rapidly emerging technologies in ambient health care is pervasive cardiac surveillance.
The availability of hardware solutions for collecting streaming information on the dynamics of heart rate of individuals during daily life may revolutionise health care. This may contribute to an understanding of complex cardiovascular diseases of heterogeneous origin, and also to a deeper understanding of human nature in complex societal tasks, by providing insight into the interdependence of physiological predisposition and individual, psychological and group human social involvement.
We welcome contributions addressing complexity measures of heart rate, as an univariate variable or in an interacting, causally coupled network setting with other variables. Of special, although not exclusive interest for this Research Topic are contributions addressing the role of various measures of entropy in the characterisation of heart rate complexity, and transfer entropy in causal combination with other physiological variables. Indeed, entropy is a binding information theoretic concept, bridging complexity with predictability, making it a measure of choice for the challenging task of capturing the complex dynamics of the cardiac regulatory system in a daily setting and providing measures of risk in cases of regulatory dysfunction.
This Research Topic welcomes all contributions to the state-of-the-art quantitative assessment of the complexity of the heart rate. In particular, with the aim of revealing and characterising the cardiovascular system's complexity, as reflected in HRV, for the prediction and prognosis of the future of the system's dynamics.