Transcript PPT - PhysioNet

National Institute of
Biomedical Imaging
and Bioengineering
An introduction to
PhysioNet
the research resource for
complex physiologic signals
National Institute
of General
Medical Sciences
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
PhysioToolkit
Archive of
Physiologic Signals
and Time Series
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?
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PhysioNet research team members
Other university-based research teams
Other hospital-based research teams
Industry
Where Do the Data Collections
Come From?
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PhysioNet research team members
Other university-based research teams
Other hospital-based research teams
Industry
You! (email [email protected])
Example of a PhysioBank Dataset
RR interval (seconds)
Record e001a
Time (hours)
Data from the NHLBI Cardiac Arrhythmia Suppression
Trial (CAST) RR Interval Sub-study Database
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.
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?
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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:
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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?
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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?
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PhysioNet research team members
Contributions from individuals and teams
around the world
PhysioNet/Computers in Cardiology annual
Challenges
You! (email [email protected])
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
Data
Software
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.
PhysioNet Fosters Key NIH Priorities
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Common infrastructures for clinical research
Complex biological systems
Computational biology and informatics
New interdisciplinary, translational research teams
Who Uses PhysioNet / Where?
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>30,000 researchers, students, manufacturers,
educators, each month
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From all 50 US states and DC
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Users from >100 other countries
Research by PhysioNet Team
Three Broad Goals:
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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
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Extensive publications by key personnel
Extensive publications by others based on
Resource (>400)
Contributions to basic mechanisms/clinical
medicine
Technology transfer
PhysioNet Impact (continued)
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International collaborations
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Incubator for NIH grant development & support
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NIH-wide influence: model for data/software
sharing & multidisciplinary translational research
Educational support: PhysioNet in the
Classroom
PhysioNet in the Classroom
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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-TexasHarvard/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
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
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Boston
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San Antonio
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Brazil
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Israel
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Italy
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Moscow
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Slovenia
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Spain
Another PhysioNet Innovation:
International Time Series Challenges
With the annual Computers in Cardiology conference,
PhysioNet hosts challenges, inviting participants to tackle
important problems:
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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
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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
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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
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