scispace - formally typeset

Journal ArticleDOI

PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.

13 Jun 2000-Circulation (Circulation)-Vol. 101, Iss: 23, pp 215-220

Abstract: —The newly inaugurated Research Resource for Complex Physiologic Signals, which was created under the auspices of the National Center for Research Resources of the National Institutes of He...
Citations
More filters

Journal ArticleDOI
TL;DR: This survey tries to provide a structured and comprehensive overview of the research on anomaly detection by grouping existing techniques into different categories based on the underlying approach adopted by each technique.
Abstract: Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.

7,894 citations


Journal ArticleDOI
24 May 2016-Scientific Data
Abstract: MIMIC-III ('Medical Information Mart for Intensive Care') is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Data includes vital signs, medications, laboratory measurements, observations and notes charted by care providers, fluid balance, procedure codes, diagnostic codes, imaging reports, hospital length of stay, survival data, and more. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework.

2,801 citations


Journal ArticleDOI
TL;DR: Application of fractal analysis may provide new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as to monitoring the aging process, and similar approaches show promise in assessing other regulatory systems, such as human gait control in health and disease.
Abstract: According to classical concepts of physiologic control, healthy systems are self-regulated to reduce variability and maintain physiologic constancy. Contrary to the predictions of homeostasis, however, the output of a wide variety of systems, such as the normal human heartbeat, fluctuates in a complex manner, even under resting conditions. Scaling techniques adapted from statistical physics reveal the presence of long-range, power-law correlations, as part of multifractal cascades operating over a wide range of time scales. These scaling properties suggest that the nonlinear regulatory systems are operating far from equilibrium, and that maintaining constancy is not the goal of physiologic control. In contrast, for subjects at high risk of sudden death (including those with heart failure), fractal organization, along with certain nonlinear interactions, breaks down. Application of fractal analysis may provide new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as to monitoring the aging process. Similar approaches show promise in assessing other regulatory systems, such as human gait control in health and disease. Elucidating the fractal and nonlinear mechanisms involved in physiologic control and complex signaling networks is emerging as a major challenge in the postgenomic era.

1,773 citations


Journal ArticleDOI
Leon Glass1Institutions (1)
08 Mar 2001-Nature
TL;DR: Molecular and physical techniques combined with physiological and medical studies are addressing questions concerning the dynamics of physiological rhythms and are transforming the understanding of the rhythms of life.
Abstract: Complex bodily rhythms are ubiquitous in living organisms. These rhythms arise from stochastic, nonlinear biological mechanisms interacting with a fluctuating environment. Disease often leads to alterations from normal to pathological rhythm. Fundamental questions concerning the dynamics of these rhythmic processes abound. For example, what is the origin of physiological rhythms? How do the rhythms interact with each other and the external environment? Can we decode the fluctuations in physiological rhythms to better diagnose human disease? And can we develop better methods to control pathological rhythms? Mathematical and physical techniques combined with physiological and medical studies are addressing these questions and are transforming our understanding of the rhythms of life.

1,126 citations


Journal ArticleDOI
TL;DR: A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals and may be employed to assess biomedical signal processing techniques which are used to compute clinical statistics from the ECG.
Abstract: A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals. The operator can specify the mean and standard deviation of the heart rate, the morphology of the PQRST cycle, and the power spectrum of the RR tachogram. In particular, both respiratory sinus arrhythmia at the high frequencies (HFs) and Mayer waves at the low frequencies (LFs) together with the LF/HF ratio are incorporated in the model. Much of the beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation are shown to result. This model may be employed to assess biomedical signal processing techniques which are used to compute clinical statistics from the ECG.

987 citations


References
More filters

Journal ArticleDOI
03 Jun 1999-Nature
Abstract: There is evidence that physiological signals under healthy conditions may have a fractal temporal structure. Here we investigate the possibility that time series generated by certain physiological control systems may be members of a special class of complex processes, termed multifractal, which require a large number of exponents to characterize their scaling properties. We report on evidence for multifractality in a biological dynamical system, the healthy human heartbeat, and show that the multifractal character and nonlinear properties of the healthy heart rate are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure.

1,396 citations


Journal ArticleDOI
01 Jan 1988-Physics Today
TL;DR: One of the most interesting features of the book is that it makes a start at explaining "dynamical diseases" that are not the result of infection by pathogens but that stem from abnormalities in the timing of essential functions.
Abstract: In an important new contribution to the literature of chaos, two distinguished researchers in the field of physiology probe central theoretical questions about physiological rhythms. Topics discussed include: How are rhythms generated? How do they start and stop? What are the effects of perturbation of the rhythms? How are oscillations organized in space? Leon Glass and Michael Mackey address an audience of biological scientists, physicians, physical scientists, and mathematicians, but the work assumes no knowledge of advanced mathematics. Variation of rhythms outside normal limits, or appearance of new rhythms where none existed previously, are associated with disease. One of the most interesting features of the book is that it makes a start at explaining "dynamical diseases" that are not the result of infection by pathogens but that stem from abnormalities in the timing of essential functions. From Clocks to Chaos provides a firm foundation for understanding dynamic processes in physiology.

1,225 citations


Journal ArticleDOI
Ary L. Goldberger1Institutions (1)
11 May 1996-The Lancet
TL;DR: An introduction to some key aspects of non-linear dynamics and selected applications to physiology and medicine is provided.
Abstract: Clinicians are increasingly aware of the remarkable upsurge of interest in non-linear dynamics, the branch of the sciences widely referred to as chaos theory. Those attempting to evaluate the biomedical relevance of this subject confront a confusing array of terms and concepts, such as non-linearity, fractals, periodic oscillations, bifurcations, and complexity, as well as chaos.\" Therefore, I hope to provide an introduction to some key aspects of non-linear dynamics and review selected applications to physiology and medicine. Linear systems are well behaved. The magnitude of their responses is proportionate to the strength of the stimuli. Further, linear systems can be fully understood and predicted by dissecting out their components. The subunits of a linear system add up-there are no surprises or anomalous behaviours. By contrast, for non-linear systems proportionality does not hold: small changes can have striking and unanticipated effects. Another complication is that non-linear systems cannot be understood by analysing their components individually. This reductionist strategy fails because the components of a non-linear network interact-ie, they are coupled. Examples include the interaction of pacemaker cells in the heart or neurons in the brain. Their non-linear coupling generates behaviours that defy explanation by traditional (linear) models such as self-sustained, periodic waves (eg, ventricular tachycardia); abrupt changes (eg, sudden onset of a seizure); and, possibly, chaos. One important class of abrupt, non-linear transitions is called a bifurcation.1,4 This term describes situations in which a very small increase or decrease in the value of some factor controlling the system causes it to change abruptly from one type of behaviour to another. A common type of bifurcation is the sudden appearance of regular oscillations that alternate between two values. This dynamic may underlie various alternans patterns in cardiovascular dysfunction. A familiar example is the beat-to-beat alternation in QRS axis and amplitude seen in some cases of cardiac tamponade.5 Many other examples of alternans in perturbed cardiac physiology have been described, including ST-T alternans that may precede ventricular fibrillation 6 and pulsus alternans during heart failure. Although the focus of much recent attention, chaos per se actually consists of only one specific subtype of non-linear dynamics.' Chaos refers to a seemingly random type of variability that can arise from the operation of even the most simple non-linear system. Because the equations that generate such erratic, and apparently unpredictable, behaviour do not contain any random terms-this mechanism is referred to as deterministic chaos.' The colloquial …

774 citations


Journal ArticleDOI
05 Aug 1997-Circulation
TL;DR: It is demonstrated that HRV analysis of ambulatory ECG recordings based on fully automated methods can have prognostic value in a population-based study and that nonlinear HRV indices may contribute prognosticvalue to complement traditional HRV measures.
Abstract: BACKGROUND: Despite much recent interest in quantification of heart rate variability (HRV), the prognostic value of conventional measures of HRV and of newer indices based on nonlinear dynamics is not universally accepted. METHODS AND RESULTS: We have designed algorithms for analyzing ambulatory ECG recordings and measuring HRV without human intervention, using robust methods for obtaining time-domain measures (mean and SD of heart rate), frequency-domain measures (power in the bands of 0.001 to 0.01 Hz [VLF], 0.01 to 0.15 Hz [LF], and 0.15 to 0.5 Hz [HF] and total spectral power [TP] over all three of these bands), and measures based on nonlinear dynamics (approximate entropy [ApEn], a measure of complexity, and detrended fluctuation analysis [DFA], a measure of long-term correlations). The study population consisted of chronic congestive heart failure (CHF) case patients and sex- and age-matched control subjects in the Framingham Heart Study. After exclusion of technically inadequate studies and those with atrial fibrillation, we used these algorithms to study HRV in 2-hour ambulatory ECG recordings of 69 participants (mean age, 71.7+/-8.1 years). By use of separate Cox proportional-hazards models, the conventional measures SD (P .3), were not. In multivariable models, DFA was of borderline predictive significance (P=.06) after adjustment for the diagnosis of CHF and SD. CONCLUSIONS: These results demonstrate that HRV analysis of ambulatory ECG recordings based on fully automated methods can have prognostic value in a population-based study and that nonlinear HRV indices may contribute prognostic value to complement traditional HRV measures.

503 citations


Journal ArticleDOI
05 Mar 1998-Nature
TL;DR: High spatial and temporal resolution mapping of optical transmembrane potentials can easily detect transiently erupting rotors during the early phase of ventricular fibrillation, characterized by a relatively high spatiotemporal cross-correlation.
Abstract: Sudden cardiac death is the leading cause of death in the industrialized world, with the majority of such tragedies being due to ventricular fibrillation1. Ventricular fibrillation is a frenzied and irregular disturbance of the heart rhythm that quickly renders the heart incapable of sustaining life. Rotors, electrophysiological structures that emit rotating spiral waves, occur in several systems that all share with the heart the functional properties of excitability and refractoriness. These re-entrant waves, seen in numerical solutions of simplified models of cardiac tissue2, may occur during ventricular tachycardias3,4. It has been difficult to detect such forms of re-entry in fibrillating mammalian ventricles5,6,7,8. Here we show that, in isolated perfused dog hearts, high spatial and temporal resolution mapping of optical transmembrane potentials can easily detect transiently erupting rotors during the early phase of ventricular fibrillation. This activity is characterized by a relatively high spatiotemporal cross-correlation. During this early fibrillatory interval, frequent wavefront collisions and wavebreak generation9 are also dominant features. Interestingly, this spatiotemporal pattern undergoes an evolution to a less highly spatially correlated mechanism that lacks the epicardial manifestations of rotors despite continued myocardial perfusion.

429 citations


Performance
Metrics
No. of citations received by the Paper in previous years
YearCitations
202240
20211,244
20201,113
2019963
2018851
2017768