2014 News
New Database added: CEBSDB
News from: Combined measurement of ECG, Breathing and Seismocardiograms v1.0.0.
Dec. 12, 2014
Combined measurement of ECG, Breathing, and Seismocardiograms DataBase, CEBSDB. A dataset of 60 records from 20 volunteers has been contributed to PhysioBank by Miguel Angel Garcia Gonzalez and Ariadna Argelagos Palou from the Universitat Politecnica de Catalunya. Each record contains two ECGs, a respiration, and a seismocardiogram signals. The database was designed to check if errors in RR series are influenced by breathing, and if there is a significant variability in RR series estimated from ECGs versus seismocardiograms.
Read more: https://doi.org/10.13026/C2KW23
New Software added to PhysioNet
Nov. 4, 2014
Two new software packages have been added to PhysioNet by Joachim Behar, Gari Clifford, and colleagues at the University of Oxford. FECGSyn is a new Foetal ECG Waveform Generator. The second package, the Random Search Toolbox, is a MATLAB toolbox for selecting model hyper-parameters via random search.
Official results for Phase III of the 2014 PhysioNet/CinC Challenge
Sept. 9, 2014
The top official results in Phase III were achieved by Alistair Johnson (87.9), Teo Soo-Kng (86.7), Thomas De Cooman (86.6), Jan GieraĆtowski (86.4), Marcus Vollmer (86.2).
Preparing your talk for Computing in Cardiology 2014
Aug. 21, 2014
Information on how to prepare your talk for Computing in Cardiology is described here.
Upcoming events: Computing Cardiology 2014 and MIT Critical Data Marathon
July 30, 2014
Two upcoming events this September at MIT will be of interest to PhysioNet users. The first is the International Critical Care Data Mining Marathon, a weekend event (5-7 September 2014). The International Critical Care Data Mining Marathon will bring together teams of engineers and clinicians to develop tools and crowd-source knowledge in clinical data, with a hands-on data mining workshop using the MIMIC-II Database.
The second event is the 2014 Computing in Cardiology conference held from September 7-10 2014 at Cambridge, Massachusetts. Computing in Cardiology is an international scientific conference that has been held annually since 1974 and hosting PhysioNet Challenges since 2000. This conference provides a forum for scientists and professionals from the fields of medicine, physics, engineering and computer science to discuss their current research in topics pertaining to computing in clinical cardiology and cardiovascular physiology.
Read more: http://cinc2014.org/
Official results for Phase II of the 2014 PhysioNet/CinC Challenge
June 25, 2014
The top official results in Phase II were achieved by Thomas De Cooman (86.2), Marcus Vollmer (86.1), Urska Pangerc (85.2), Filip Plesinger (85.0), and Alistair Johnson (84.6).
Official results for Phase I of the 2014 PhysioNet/CinC Challenge
April 17, 2014
The top official results in Phase I were achieved by Marcus Vollmer (93.2), Urska Pangerc (89.2), Lars Johannesen (88.9), Quan Ding (88.9), and Teo Soo-Kng (88.7). Several other high-scoring entries were disqualified for reasons described in the FAQs.
National Sleep Research Resource
April 4, 2014
Read more: http://sleepdata.org/
Biometric Human Identification based on ECG
News from: ECG-ID Database v1.0.0.
March 6, 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 ECGs in her master's thesis. 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.
Read more: https://doi.org/10.13026/C2J01F
ERP-based Brain-Computer Interface recordings
News from: ERP-based Brain-Computer Interface recordings v1.0.0.
March 4, 2014
This dataset, 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.
Read more: https://doi.org/10.13026/C2101S
Motion Artifact Contaminated fNIRS and EEG Data
News from: Motion Artifact Contaminated fNIRS and EEG Data v1.0.0.
March 3, 2014
This data collection, contributed to PhysioNet by Kevin Sweeney and colleagues at the National University of Ireland in Maynooth, 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.
Read more: https://doi.org/10.13026/C2988P
CTU-UHB Intrapartum Cardiotocography Database
News from: CTU-CHB Intrapartum Cardiotocography Database v1.0.0.
Feb. 18, 2014
This collection of 552 CTGs from the Czech Technical University (CTU) in Prague and the University Hospital in Brno (UHB) was carefully selected from 9164 recordings recently collected at UHB. Each recording is up to 90 minutes long, and includes a fetal heart rate time series, a uterine contraction signal, and maternal, delivery, and fetal clinical details.
Read more: https://doi.org/10.13026/C22013
Simulated Fetal Phonocardiograms
News from: Simulated Fetal Phonocardiograms v1.0.0.
Jan. 30, 2014
A contribution of simulated fetal PCGs 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.
Read more: https://doi.org/10.13026/C2GW25
Robust Detection of Heart Beats in Multimodal Data
Jan. 7, 2014
Read more: https://physionet.org/challenge/2014/