from PhysioNet, the research resource for complex physiologic signals


What's New on PhysioNet?

WFDB Software Package Over 70 open-source applications for signal processing, analysis, and more, all built on a stable and easy-to-use library that can be incorporated into your own software. Latest update: Thursday, 13 March 2014 (summary here).
3 November 2014 Two new software packages have been added to the PhysioTookit library. FECGSyn is a new Foetal ECG Waveform Generator contributed by Joachim Behar and colleagues in Gari Clifford's group at the University of Oxford. The second package, the Random Search Toolbox, is a MATLAB toolbox for selecting model hyper-parameters via random search, also contributed by Joachim Behar and colleagues in Gari Clifford's group.
4 April 2014 PhysioNet users with an interest in sleep physiology now have access to the web site of the National Sleep Research Resource (NSRR), which hosts large annotated collections of EDF polysomnograms and related clinical data elements from well-characterized research cohorts and clinical trials. The first data set available includes over 8,000 studies from exams 1 and 2 of the Sleep Heart Health Study, with scheduled new data releases every quarter from additional data sets. NSRR also provides open-source software for viewing and analyzing these data.
6 March 2014 The ECG-ID Database is a set of 310 ECGs from 90 volunteers, created and contributed to PhysioBank by Tatiana Lugovaya, who used the data in her master's thesis on the topic of biometric human identification using the ECG. An excellent summary of this thesis, with a discussion of the challenges in using ECGs as biometrics, and a comparison of the author's methods and results with those of three previous studies, is also available.
4 March 2014 A set of high-resolution multichannel EEG recordings — created and contributed by Luca Citi, Riccardo Poli, and Caterina Cinel — was generated as part of a study aimed at identifying the factors limiting the performance of brain-computer interfaces (BCIs) based on event-related potentials (ERPs), in order to improve the transfer rate and the usability of these interfaces. Twenty recordings of each of 10 participants include annotated 64-channel EEGs and 4-channel EOGs, generated while the participants focused on specified target characters displayed by a traditional matrix speller.
3 March 2014 A collection of motion artifact contaminated fNIRS and EEG data has been contributed to PhysioBank by Kevin Sweeney and colleagues at the National University of Ireland in Maynooth. The data set contains examples of functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) recordings that have been created for evaluating artifact removal methods. In each such recording, one or two pairs of similar physiological signals have been acquired from transducers in close proximity. One signal of each pair is contaminated by motion artifact, documented in each case by simultaneously recorded outputs of 3-axis accelerometers affixed to each transducer.
18 February 2014 The CTU-UHB Intrapartum Cardiotocography Database, from the Czech Technical University (CTU) in Prague and the University Hospital in Brno (UHB), contains 552 cardiotocography (CTG) recordings, which were carefully selected from 9164 recordings collected between 2010 and 2012 at UHB. The CTG recordings start no more than 90 minutes before actual delivery, and each is at most 90 minutes long. Each CTG contains a fetal heart rate (FHR) time series and a uterine contraction (UC) signal, each sampled at 4 Hz. Each CTG is accompanied by maternal, delivery, and fetal clinical details.
30 January 2014 A contribution of simulated fetal phonocardiograms is now available in PhysioBank. The synthetic PCGs exhibit a realistic range of signal-to-noise ratios, with simulated maternal heart and organ sounds, fetal movements, and environmental sounds.
7 January 2014 The 15th annual PhysioNet/CinC Challenge, Robust Detection of Heart Beats in Multimodal Data, is now underway. Read the first announcement, and study the training data set and a sample entry.
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