Research Resource for Complex Physiologic Signals

Research Resource for Complex Physiologic Signals

Research Emphasis

The objective of this resource (Beth Israel Deaconess Medical Center/Harvard Medical School and Massachusetts Institute of Technology, Division of Health Sciences and Technology) is to accelerate current research progress and catalyze new investigations in the quantitative study of complex physiologic signals. The resource has three interdependent components: PhysioBank, PhysioToolkit, and PhysioNet. PhysioBank is a large and growing archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multiparameter cardiopulmonary, neural, and other signals from healthy subjects and from patients with a variety of conditions with major public health implications, including life-threatening arrhythmias, sleep apnea, neurologic disorders, and aging. PhysioToolkit is a library of open-source software for physiologic signal processing, analysis, and detection of physiologically significant events with the use of both classic techniques and novel methods based on statistical physics and nonlinear dynamics. PhysioNet is an online forum for the dissemination and exchange of recorded biomedical signals and open-source software for analyzing them.

Current Research

The resource is developing new algorithms that quantify the transient and local properties of nonstationary physiologic signals and the cross-interactions among multiparameter signals. These techniques will be used to detect changes that may precede the onset of catastrophic physiologic events, including epilepsy and sudden cardiac death. Complementary studies are aimed at developing techniques to quantify the nonlinear dynamics of physiologic control, with an emphasis on modeling these mechanisms and identifying new measures that have diagnostic or prognostic utility in life-threatening pathologies, such as sleep apnea and congestive heart failure. A related core area of research is the development of methods for measuring the nonlinear complexity of physiologic signals and the loss of complexity with aging and disease.

Resource Capabilities

Methods

The PhysioNet Web site creates an online community for the dissemination and exchange of recorded biomedical signals and the software for analyzing them by providing facilities for cooperative analysis of data and evaluation of proposed new algorithms. Much of the PhysioBank and PhysioToolkit software utilizes standard networking protocols, which allows interactive display and analysis of physiologic signals at remote locations on the Internet.

Software

PhysioToolkit is a large and growing library of software for physiologic signal processing, analysis, and detection of physiologically significant events with the use of both classic techniques and novel methods based on statistical physics and nonlinear dynamics, interactive display and characterization of signals, creation of new databases, simulation of physiologic and other signals, quantitative evaluation and comparison of analysis methods, and analysis of nonequilibrium and nonstationary processes. A unifying theme of the research projects that contribute software to PhysioToolkit is the extraction of "hidden" information from biomedical signals, information that may have diagnostic or prognostic value in medicine, or explanatory or predictive power in basic research. All PhysioToolkit software is available in source form under the GNU General Public License. More than 80 packages are available.

Special Features

PhysioBank is a large and growing archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multiparameter 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. PhysioBank now contains more than 40 databases that may be freely downloaded.

Available Resources

The resource has also produced an extensive set of tutorialstutorials and reference materials documenting its software and data collections; currently, these include 14 tutorials and 6 books, all of which are available online. Please consult the regularly updated list of Frequently Asked Questions about PhysioNet.

For researchers wishing to explore the data collections and those who need relatively small amounts of data, the resources Web applications make it possible to view any of the available data and to obtain data excerpts in text format using only a Web browser.

Training Opportunities and Workshops

In cooperation with the annual Computers in Cardiology conference, PhysioNet hosts a series of challenges, inviting participants to tackle clinically interesting problems that are either unsolved or not well-solved. Topics to date have included detecting sleep apnea with an electrocardiogram, predicting paroxysmal atrial fibrillation, RR interval time series modeling, distinguishing ischemic from nonischemic ST changes, predicting spontaneous termination of atrial fibrillation, and automated measurement of QT intervals. For each challenge, the resource assembles the raw materials needed to begin work and posts them on PhysioNet. The challenges typically attract 10 to 20 teams of participants (although the current challenge in progress, on QT interval measurement, has more than 30 active teams), and the results are discussed in dedicated scientific sessions at the Computers in Cardiology conference. Well over 100 publications, notably including follow-up studies by collaborating participants, have resulted from these challenges.

In conjunction with Beth Israel Deaconess Medical Center and the Harvard Medical School Department of Continuing Medical Education, resource members have initiated a course on complex physiologic signals. Information about the first offering in this unique series (Heart Rate Variability 2006), held April 2006 in Boston, MA, is available on the Ongoing and Coming Events page of the PhysioNet Web site. Curricular material is also included.

Publications

1. Yang, A. C., Goldberger, A. L., and Peng, C. K., Genomic classification using a new information-based similarity index: Application to the SARS coronavirus. Journal of Computational Biology 12:1103–1116, 2005.

2. Costa, M., Goldberger, A. L., and Peng, C. K., Broken asymmetry of the human heartbeat: Loss of time irreversibility in aging and disease. Physical Review Letters 95:198102, 2005.

3. Costa, M., Goldberger, A. L., and Peng, C. K., Multiscale entropy analysis of biological signals. Physical Review E 71:021906, 2005.

4. Thomas, R. J., Mietus, J. E., Peng, C. K., and Goldberger, A. L., An electrocardiogram-based technique to assess cardiopulmonary coupling during sleep. Sleep 28:1135–1143, 2005.

5. Goldberger, A. L., Amaral, L. A. N., et al., Fractal dynamics in physiology: Alterations with disease and aging. Proceedings of the National Academy of Sciences USA 99:2466–2472, 2002.

6. Moody, G. B., Mark, R. G., and Goldberger, A. L., PhysioNet: A web-based resource for the study of physiologic signals. IEEE Engineering in Medicine and Biology 20:70–75, 2001.