An introduction to PhysioNet the research resource for complex physiologic signals
What is PhysioNet? • A unique web-based resource funded by NIH, intended to support current research and stimulate new investigations in the study of complex biomedical and physiologic signals. • Three closely interdependent components: • Data repository (PhysioBank) • Library of related software (PhysioToolkit) • Free-access website (physionet.org)
Why Study Signals? Physiologic signals and time series reveal aspects of health, disease, biotoxicity and aging not captured by static measures. Raw (original) signals are of increasing interest as means of developing new biomarkers, of measuring parameters of known interest, and also for developing new insights into basic mechanisms of human physiology.
Resource Established September,1999 Founded under auspices of NCRR (1999-2007). Now supported by NIBIB and NIGMS (2007-2012) under Cooperative Agreement U01EB008577
Design of the PhysioNet Website Scientific Community-at-Large PhysioNet Gateway to the Resource PhysioBank Archive of Physiologic Signals and Time Series PhysioToolkit Open Source Software For Data Analysis
What is PhysioBank? PhysioBank currently includes: >40 collections of cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging.
Where Do the Data Collections Come From? PhysioNet research team members Other university-based research teams Other hospital-based research teams Industry
Where Do the Data Collections Come From? PhysioNet research team members Other university-based research teams Other hospital-based research teams Industry You! (email email@example.com)
Record e001a Record e001a RR interval (seconds) RR interval (seconds) Time (hours) Time (hours) Example of a PhysioBank Dataset Physiologic time series, such as this series of cardiac interbeat (RR) intervals measured over 24 hours, can capture some of the information lost in summary statistics. Data from the NHLBI Cardiac Arrhythmia Suppression Trial (CAST) RR Interval Sub-study Database
Another PhysioBank Dataset Many data collections in PhysioBank come from published studies Hausdorff et al., J Appl Physiol 86(3)1040-7 (1999)
Viewing PhysioBank Data Chart-O-Matic allows you to view "chart recording" samples of any PhysioBank record. The web application requires no client-side software other than a web browser.
What Can You Do with PhysioBank Data? Download for exploration and research Develop new signal processing algorithms Evaluate algorithms using ‘standard’ data Test physiologic models Develop/test/refine new biomarkers Create “real-world” classroom challenges at undergraduate, graduate and post-graduate levels
What is PhysioToolkit? Open-source software for physiologic signal processing and analysis: Detection of physiologically significant events using both classical techniques and novel methods Interactive display & characterization of signals; creation of new databases Physiologic signal modelling and for quantitative evaluation and comparison of analysis methods
Where Does the Open-Source Software Come From? PhysioNet research team members Contributions from individuals and teams around the world PhysioNet/Computers in Cardiology annual Challenges
Where Does the Open-Source Software Come From? PhysioNet research team members Contributions from individuals and teams around the world PhysioNet/Computers in Cardiology annual Challenges You! (email firstname.lastname@example.org)
Open Source Tools: WFDB Software Projects requiring large amounts of data can process them efficiently using WFDB software. The WFDB library reads and writes annotations and signals in many commonly-used binary formats, providing uniform access to data from local disks and from the web.
Some PhysioNet Contributions Include Both Data and Software Manuscript Software Data
More Contributions with Data & Software Manuscript Data Software
PhysioNet Provides Tutorials on Complex Signal Analysis Downloads since 2004: MSE code 4,208; MSE tutorial 7,432 Method featured in Nature News and Views 2002; 419:263.
Common infrastructures for clinical research Complex biological systems Computational biology and informatics New interdisciplinary, translational research teams PhysioNet Fosters Key NIH Priorities
>30,000 researchers, students, manufacturers, educators, each month From all 50 US states and DC Users from >100 other countries Who Uses PhysioNet / Where?
Research by PhysioNet Team Three Broad Goals: Relating complex dynamics of physiologic time series to underlying mechanisms inhealth, disease, and aging Developing diagnostic and prognostic biomarkers of complex dynamics that quantify control system functions and pathologies Detecting and forecasting major events, such as seizures, sudden cardiac arrest, falls, hemodynamic collapse, and apneas, and generating hypotheses about their mechanisms
Assessing PhysioNet’s Impact Extensive publications by key personnel Extensive publications by others based on Resource (>400) Contributions to basic mechanisms/clinical medicine Technology transfer
PhysioNet Impact (continued) International collaborations Incubator for NIH grant development & support NIH-wide influence: model for data/software sharing & multidisciplinary translational research Educational support: PhysioNet in the Classroom
Increasing use of PhysioNet in undergraduate and graduate level courses in bioengineering and other disciplines Example: “Gait Module for Freshman-Level Introductory Course in Biomedical Engineering”* Part of challenge-based approach developed by University of Memphis in partnership with Vanderbilt-Northwestern-Texas-Harvard/MIT Engineering Research Center (VaNTH ERC) *See: Proc 2005 Am Soc Eng Education Ann Conf PhysioNet in the Classroom
World-wide Network of Mirror Sites Boston San Antonio Brazil Israel Italy Moscow Slovenia Spain • Provide distributed access and backup to PhysioNet • Established and maintained by volunteers at no cost to the Resource • Setup is easy; open source software; upkeep is automated
Another PhysioNet Innovation: International Time Series Challenges • With the annual Computers in Cardiology conference, PhysioNet hosts challenges, inviting participants to tackle important problems: • Detecting Sleep Apnea from the ECG • Predicting Paroxysmal Atrial Fibrillation • RR Interval Time Series Modeling • Distinguishing Ischemic from Non-Ischemic ST Changes • Spontaneous Termination of Atrial Fibrillation • QT Interval Measurement • ECG Imaging of Myocardial Infarction
Getting Started: Take PhysioTour! > 750,000 visitors!
PhysioNet: Looking Ahead New database and software additions New infrastructures for database development and data sharing (PhysioNet Works) New PhysioNet/Computers in Cardiology Challenge Multiscale analysis & modelling Development of new dynamical biomarkers
Faces of PhysioNet 1 4 5 6 1-George Moody 2-Roger Mark 3-Gari Clifford 4-Mohammed Saeed 5-Mauricio Villarroel 6-C-K Peng 7-Madalena Costa 8-Joe Mietus 9-Ary Goldberger 8 7 9