PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.
TL;DR: The newly inaugurated Research Resource for Complex Physiologic Signals (RRSPS) as mentioned in this paper was created under the auspices of the National Center for Research Resources (NCR Resources).
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...
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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.
9,627 citations
TL;DR: The Medical Information Mart for Intensive Care (MIMIC-III) as discussed by the authors is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital.
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.
4,056 citations
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.
1,905 citations
TL;DR: It is demonstrated that an end-to-end deep learning approach can classify a broad range of distinct arrhythmias from single-lead ECGs with high diagnostic performance similar to that of cardiologists.
Abstract: Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG workflow1. Widely available digital ECG data and the algorithmic paradigm of deep learning2 present an opportunity to substantially improve the accuracy and scalability of automated ECG analysis. However, a comprehensive evaluation of an end-to-end deep learning approach for ECG analysis across a wide variety of diagnostic classes has not been previously reported. Here, we develop a deep neural network (DNN) to classify 12 rhythm classes using 91,232 single-lead ECGs from 53,549 patients who used a single-lead ambulatory ECG monitoring device. When validated against an independent test dataset annotated by a consensus committee of board-certified practicing cardiologists, the DNN achieved an average area under the receiver operating characteristic curve (ROC) of 0.97. The average F1 score, which is the harmonic mean of the positive predictive value and sensitivity, for the DNN (0.837) exceeded that of average cardiologists (0.780). With specificity fixed at the average specificity achieved by cardiologists, the sensitivity of the DNN exceeded the average cardiologist sensitivity for all rhythm classes. These findings demonstrate that an end-to-end deep learning approach can classify a broad range of distinct arrhythmias from single-lead ECGs with high diagnostic performance similar to that of cardiologists. If confirmed in clinical settings, this approach could reduce the rate of misdiagnosed computerized ECG interpretations and improve the efficiency of expert human ECG interpretation by accurately triaging or prioritizing the most urgent conditions. Analysis of electrocardiograms using an end-to-end deep learning approach can detect and classify cardiac arrhythmia with high accuracy, similar to that of cardiologists.
1,632 citations
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.
1,204 citations
References
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08 Sep 1996
TL;DR: The MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database is intended to meet the needs of automated decision support systems and to make the database available to other researchers shortly thereafter.
Abstract: Development and evaluation of automated decision support systems requires large amounts of well-characterized, reproducible test data. The MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database is intended to meet these needs. The database, currently nearing completion, will include 100 patient records, each typically containing between 24 and 48 hours of continuous data recorded from patient monitors in the medical, surgical, and cardiac intensive care units of Boston's Beth Israel Hospital. Each record will be accompanied by detailed clinical data derived from the patient's medical record and from the hospital's on-line medical information systems. We select patients to record from those likely to be hemodynamically unstable during the planned recording period. We expect to complete the selection of the recordings to be included in the database by the end of 1996, and to make the database available to other researchers shortly thereafter.
228 citations
TL;DR: For both waveforms, the postshock activation fronts after the shocks were markedly different from those just before the shock and exhibited either a focal origin or unidirectional conduction.
Abstract: To study the mechanism of defibrillation and the reason for the increased defibrillation efficacy of biphasic waveforms, the potential gradient in a 32 x 30-mm region of the right ventricle in 15 dogs was progressively lowered in four steps while a strong potential gradient field was maintained throughout the rest of the ventricular myocardium. The volume of right ventricle beneath the plaque was 10 +/- 2% of the total ventricular mass. A 10-msec monophasic (eight dogs) or 5/5-msec biphasic (seven dogs) truncated exponential shock 30% above the defibrillation threshold voltage was given via electrodes on the left ventricular apex and right atrium to create the strong potential gradient field. Simultaneously, a weaker shock with the same waveform but opposite polarity was given via mesh electrodes on either side of the small right ventricular region to cancel part of the potential difference in the region and to create one of the four levels of potential gradient fields. Shock potentials and activations were recorded from 117 epicardial electrodes in the small region, and in one dog global epicardial activations and potentials were recorded from a sock containing 72 electrodes. Each gradient field was tested 10 times for successful defibrillation after 10 seconds of electrically induced fibrillation. For both monophasic and biphasic shocks, the percentage of successful defibrillation attempts decreased (p < 0.05) as the potential gradient decreased in the small region. Defibrillation was successful approximately 80% of the time for a mean +/- SD potential gradient of 5.4 +/- 0.8 V/cm for monophasic shocks and 2.7 +/- 0.3 V/cm for biphasic shocks (p < 0.05). No postshock activation fronts arose from the small region for eight waveform when the gradient was more than 5 V/cm. For both waveforms, the postshock activation fronts after the shocks were markedly different from those just before the shock and exhibited either a focal origin or unidirectional conduction.(ABSTRACT TRUNCATED AT 400 WORDS)
188 citations
TL;DR: The results suggest that fibrillation is similar to a nonchaotic random signal, however, it is noted that such random-looking butNonchaotic behavior can also be generated by a nonlinear deterministic system.
Abstract: Ventricular fibrillation is examined to determine whether it is an instance of deterministic chaos. Surface ECGs from dogs in fibrillation were used to generate a state space representation of fibrillation. Our analysis failed to identify a low-dimensional attractor that could be associated with fibrillation. The results suggest that fibrillation is similar to a nonchaotic random signal. We note, however, that such random-looking but nonchaotic behavior can also be generated by a nonlinear deterministic system.
175 citations
TL;DR: In this article, a general approach to the question of how biological rhythms spontaneously self-regulate, based on the concept of ''stochastic feedback'' is proposed, and the model generates complex dynamics and successfully accounts for key characteristics of cardiac variability, including the $1/f$ power spectrum, the functional form and scaling of the distribution of variations.
Abstract: We propose a general approach to the question of how biological rhythms spontaneously self-regulate, based on the concept of ``stochastic feedback''. We illustrate this approach by considering the neuroautonomic regulation of the heart rate. The model generates complex dynamics and successfully accounts for key characteristics of cardiac variability, including the $1/f$ power spectrum, the functional form and scaling of the distribution of variations, and correlations in the Fourier phases. Our results suggest that in healthy systems the control mechanisms operate to drive the system away from extreme values while not allowing it to settle down to a constant output.
154 citations
TL;DR: The purpose of this study was to assess the feasibility and safety of intracardiac echocardiography to guide transseptal puncture for radiofrequency catheter ablation.
Abstract: Transseptal Catheterization. Introduction: The purpose of this study was to asess the feasibility and safety of intracardiac echocardiography to guide transseptal puncture for radiofrequency catheter ablation.
Methods and Results: Transcatheter intracardiac echocardiography (9 MHz) was utilized to guide transseptal puncture in 53 patients undergoing radiofrequency catheter ablation. The anatomy and relationship of intra- and extracardiac structures were visualized with the ultrasound transducer positioned at the fossa ovalis. The tip of the transseptal dilator and tenting of the fossa ovalis and the left atrial wall were simultaneously visualized in a single ultrasound image in all patients. With maximum tenting of the fossa ovalis, the mean distance from the fossa to the left atrial wall was 11.9 ± 5.8 mm (range: 1.8 to 25.6 mm). In four patients (8%), the tented fossa ovalis abutted the left atrial wall and the transseptal dilator was redirected with ultrasound guidance. Puncture of the interatrial septum was achieved through the fossa ovalis in each patient and required a single attempt in 51 patients (96%). The mean number of punctures per patient was 1.1 ± 0.4. The mean time to perform transseptal catheterization was 18.2 ± 6.8 minutes. There were no complications.
Conclusion: Intracardiac echocardiography delineated the anatomy of intra- and extracardiac structures not identified with fluoroscopy and simplified correct positioning of the transseptal dilator, puncture of the fossa ovalis, and cannulation of the left atrium in a timely and uncomplicated fashion.
149 citations