National Institute of General Medical Sciences

National Institute of Biomedical Imaging and Bioengineering

An introduction to

PhysioNetthe 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 (1999-2007). Now supported by NIBIB and NIGMS (2007-2012) under Cooperative Agreement U01EB008577

Design of the PhysioNet Website

PhysioToolkitPhysioToolkitOpen Source Open Source

SoftwareSoftwareFor Data AnalysisFor Data Analysis

PhysioNetPhysioNetGateway to the Gateway to the

ResourceResource

PhysioBankPhysioBankArchive of Archive of

Physiologic Signals Physiologic Signals and Time Seriesand Time Series

Scientific Community-at-LargeScientific 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! (email webmaster@physionet.org)

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

inte

rval

(se

con

ds)

Record e001a

Time (hours)

RR

inte

rval

(se

con

ds)

Record e001a

Many data collections inPhysioBank come frompublished studies

Hausdorff et al., J Appl Physiol 86(3)1040-7 (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! (email webmaster@physionet.org)

Projects requiring largeamounts 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

SoftwareData

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 7,432Method 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

1 4

1-George Moody2-Roger Mark3-Gari Clifford4-Mohammed Saeed5-Mauricio Villarroel6-C-K Peng7-Madalena Costa8-Joe Mietus9-Ary Goldberger

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