New software package added to PhysioToolkit: Data Chromatix
9 November, 2015 12:00:00 AM EST
Data Chromatix is a technique for
visualizing trends in biomedical signals by bringing memory of the
system's past behavior into the current display window. This package
was developed at the Wyss Institute at Harvard by A. Burykin, S.
Mariani, T. Silva and T. Henriques, and is described in "Remembrance of
time series past: simple chromatic method for visualizing trends in
biomedical signals," Burykin A, Mariani S, Henriques T, Silva TF,
Schnettler WT, Costa MD, Goldberger AL. Physiol Meas 2015;36(7):N95.
New software package added to PhysioToolkit: ECG-kit
9 November, 2015 12:00:00 AM EST
toolbox is a collection of MATLAB tools that Mariano Llamedo Soria used,
adapted or developed during his PhD and post-doc work with the Besicos
group at University of Zaragoza, Spain and at the National Technological
University of Buenos Aires, Argentina. The main feature of this toolbox
is that it allows the use of several popular algorithms for ECG
processing, including: Algorithms from Physionet's WFDB software
package; QRS detectors, such as gqrs, wqrs, wavedet, ecgpuwave, Pan &
Tompkins, EP limited; Wavelet-based ECG delineator; Pulse wave detectors
as wabp and wavePPG; and a2hbc and EP limited heartbeat classifiers.
New Database Added: SHAREEDB
19 May, 2015 06:00:00 PM EST
Smart Health for Assessing the Risk of Events via ECG (SHAREE database). The SHAREE database was developed in order to investigate the possibility of identifying hypertensive subjects at higher risk to develop vascular events based on Heart Rate Variability analysis. The database was created by Paolo Melillo, Raffaele Izzo, Ada Orrico, Paolo Scala, Marcella Attanasio, Marco Mirra, Nicola De Luca, and Leandro Pecchia as part of the “Smart Health and Artificial intelligence for Risk Estimation” (SHARE) project, which seeks ways to prevent cardiovascular events and falls in people over 65.
New Database Added: EHGDB
9 May, 2015 12:00:00 AM EST
Icelandic 16-electrode Electrohysterogram Database (EHGDB). A new dataset of 122 16-electrode EHG recordings performed on 45 pregnant Icelandic women has been published in PhysioBank. The data was contributed by Ásgeir Alexandersson, who performed the recordings at Akureyri Primary Health Care Centre, Akureyri Hospital and Landspitali University Hospital. A detailed description of the database has been published in Nature's new journal Scientific Data 2, Article number: 150017 (2015).
PhysioNet/CinC Challenge 2015
15 February, 2015 12:00:00 AM EST
The PhysioNet/Computing in Cardiology Challenge 2015 is now open.
This year's challenge is 'Reducing False Arrhythmia Alarms in the
ICU'. False alarms in the ICU can lead to a disruption of care,
impacting both the patient and the clinical staff through noise
disturbances, desensitization to warnings and slowing of response
times, leading to decreased quality of care. To address this issue,
competitors are challenged to devise a method of processing all the
available data to reduce false alarms with minimal or no effect on
true (vital) alarms.
New software packages added to PhysioToolkit!
31 January, 2015 12:00:00 PM EDT
Two new software packages have been added to PhysioToolkit! The first package, D3Maps, is a tool for visualizing the behavior of complex systems by means of the dynamical density delay mapping technique. This package was developed at the Wyss Institute by A. Burykin, L. Citi, M.D. Costa and A.L. Goldberger. The second software package, Multiscale Multifractal Analysis, is a time series analysis method designed to describe scaling properties of fluctuations within a signal. The software package was contributed by Jan Gierałtowski from Warsaw University of Technology.
PhysioNet approved as repository
for Nature's Scientific Data!
23 January 2015 12:00:00 AM EDT
PhysioNet is pleased to announce that we are now an officially recommended repository for the journal Scientific Data (SciData). SciData is an open-access, peer-reviewed publication from the Nature Publishing Group focusing on scientifically valuable research datasets. SciData's primary article-type, the Data Descriptor, is designed to make your data more discoverable, interpretable and reusable. Users who have contributed data to PhysioNet are now invited to submit their unpublished data as a Data Descriptor to Scientific Data! Pre-submission enquires are welcome at firstname.lastname@example.org.
[ more ]