National Institute of General Medical Sciences National Institute of Biomedical Imaging and Bioengineering An introduction to PhysioNet the research resource for complex physiologic signals

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) What is PhysioNet?

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 ( ). Now supported by NIBIB and NIGMS ( ) under Cooperative Agreement U01EB008577

Design of the PhysioNet Website PhysioToolkit Open Source Software For Data Analysis PhysioNet Gateway to the Resource PhysioBank Archive of Physiologic Signals and Time Series Scientific Community-at-Large

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. What is PhysioBank?

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! (

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 Example of a PhysioBank Dataset Time (hours)‏ RR interval (seconds)‏ Record e001a Time (hours)‏ RR interval (seconds)‏ Record e001a

Many data collections in PhysioBank come from published studies Hausdorff et al., J Appl Physiol 86(3) (1999) Another PhysioBank Dataset

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. Viewing PhysioBank Data

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! (

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. Open Source Tools: WFDB Software

Some PhysioNet Contributions Include Both Data and Software Software Data Manuscript

More Contributions with Data & Software Software Data Manuscript

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

Who Uses PhysioNet / Where?  >30,000 researchers, students, manufacturers, educators, each month  From all 50 US states and DC  Users from >100 other countries

Research by PhysioNet Team Three Broad Goals:  Relating complex dynamics of physiologic time series to underlying mechanisms in health, 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

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

Unofficial Metric of PhysioNet’s Use

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

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 Another PhysioNet Innovation: International Time Series Challenges

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 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