PhysioNet, established in 1999 as the NIH-sponsored Research Resource for Complex Physiologic Signals, has attained a preeminent status among data and software resources in biomedicine. Its data archive, PhysioBank, was the first, and remains the world's largest, most comprehensive and most widely used repository of time-varying physiologic signals. Its software collection, PhysioToolkit, supports exploration and quantitative analyses of PhysioBank and similar data with a wide range of well-documented, rigorously tested, open-source software that can be run on any platform. PhysioNet's team of researchers leverages results of other funded projects to drive the creation and enrichment of: " Data collections that provide increasingly comprehensive, multifaceted views of pathophysiology over long time intervals, such as the MIMIC II (Multiparameter Monitoring in Intensive Care) Database of critical care patients; " Analytic methods that lead to more timely and accurate diagnoses (such as prediction of acute hypotensive events), and elucidation of dynamical changes associated with disease and aging (such as cardiopulmonary interactions during sleep disordered breathing syndrome); " User interfaces, reference materials and services that add value and improve accessibility to PhysioNet's data and software (such as PhysioNetWorks, a virtual laboratory for data sharing). Impact: PhysioNet is a proven enabler and accelerator of innovative research by specialists, young investigators and trainees alike, working on independent projects and focused biomedical engineering challenges made possible by data that are inaccessible otherwise. Through its PhysioNetWorks, the Resource gives researchers new tools and the opportunity not merely to meet NIH data sharing mandates, but to enrich the data commons with accessible, valuable contributions. By providing free access to its unique and wide- ranging data and software collections, PhysioNet enables studies that lead to an average of 70 scholarly publications per month (well over 5000 studies since its inception by academic, clinical, and industry-affiliated researchers worldwide.
Specific aims : For the next 5 years we aim to: 1. Accelerate PhysioNet's growth with new technology and data; 2. Drive relevant innovation through a vigorous research program on complex physiologic signals; 3. Stimulate and challenge a growing community of investigators.
PhysioNet, the Research Resource for Complex Physiological Signals, maintains the world's largest, most comprehensive, and most widely used repository of time-varying physiological signals and associated signal-processing software, and makes them freely available to the research community. PhysioNet is a proven enabler and accelerator of innovative research by specialists and non- specialists alike, working on independent projects and focused engineering challenges made possible by data that are inaccessible otherwise.
|Clifford, Gari D; Silva, Ikaro; Behar, Joachim et al. (2014) Non-invasive fetal ECG analysis. Physiol Meas 35:1521-36|
|Chang, Joshua; Paydarfar, David (2014) Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm. J Comput Neurosci 37:569-82|
|Costa, Madalena D; Schnettler, William T; Amorim-Costa, Celia et al. (2014) Complexity-loss in fetal heart rate dynamics during labor as a potential biomarker of acidemia. Early Hum Dev 90:67-71|
|Costa, Madalena D; Henriques, Teresa; Munshi, Medha N et al. (2014) Dynamical glucometry: use of multiscale entropy analysis in diabetes. Chaos 24:033139|
|Cui, Xingran; Peng, Chung-Kang; Costa, Madalena D et al. (2014) Development of a new approach to quantifying stepping stability using ensemble empirical mode decomposition. Gait Posture 39:495-500|
|Burykin, Anton; Costa, Madalena D; Citi, Luca et al. (2014) Dynamical density delay maps: simple, new method for visualising the behaviour of complex systems. BMC Med Inform Decis Mak 14:6|
|Subramaniam, Balachundhar; Khabbaz, Kamal R; Heldt, Thomas et al. (2014) Blood pressure variability: can nonlinear dynamics enhance risk assessment during cardiovascular surgery? J Cardiothorac Vasc Anesth 28:392-7|
|Goldberger, Zachary D; Creutzfeldt, Claire J; Goldberger, Ary L (2014) Catastrophic neurologic syndrome with dramatic ECG changes. J Electrocardiol 47:80-3|
|Thomas, Robert Joseph; Mietus, Joseph E; Peng, Chung-Kang et al. (2014) Relationship between delta power and the electrocardiogram-derived cardiopulmonary spectrogram: possible implications for assessing the effectiveness of sleep. Sleep Med 15:125-31|
|Stirling, Leia A; Lipsitz, Lewis A; Qureshi, Mona et al. (2013) Use of a tracing task to assess visuomotor performance: effects of age, sex, and handedness. J Gerontol A Biol Sci Med Sci 68:938-45|
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