The objective of this project is to accelerate current research progress and catalyze new investigations in the study of complex biomedical signals by establishing a national biotechnology resource via an integrated approach. The proposed National Resource for Complex Biomedical Signals has three closely interdependent components: PhysioBank: This research/database component will develop and maintain: 1) a national archive of well-characterized physiological signals for use by the biomedical community; and 2) a standardized database structure and software for the creation of new databases. PhysioBank will initially emphasize the development of databases and software for the creation of new databases. PhysioBank will initially emphasize the development of 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. Core research supporting this component will also develop novel signal-processing tools for multiparameter data. PhysioLab: This research components will develop and support a library of software and new techniques for signal processing and analysis, interactive display and characterization of signals, and quantitative evaluation of analysis based on statistical physics and non-linear dynamics to detect physiologically significant events, and analyze non- equilibrium and non-stationary processes. A unifying theme of these research projects 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. PhysioNet: This component aims to establish an on-line forum for dissemination and exchange of recorded biomedical signals and software for analyzing them, by providing facilities for cooperative analysis of data and evaluation of proposed new algorithms. This forum will be made available on the World Wide Web (and in CD-ROM format). As a service and training component of this forum, we will provide on-line tutorials to assist investigators, clinicians, and students in making the best use of this Resource.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR013622-03
Application #
6394708
Study Section
Special Emphasis Panel (ZRG1-SSS-9 (20))
Program Officer
Marron, Michael T
Project Start
1999-09-03
Project End
2004-06-30
Budget Start
2001-07-01
Budget End
2002-06-30
Support Year
3
Fiscal Year
2001
Total Cost
$1,182,154
Indirect Cost
Name
Beth Israel Deaconess Medical Center
Department
Type
DUNS #
076593722
City
Boston
State
MA
Country
United States
Zip Code
02215
Clifford, Gari D; Silva, Ikaro; Moody, Benjamin et al. (2016) False alarm reduction in critical care. Physiol Meas 37:E5-E23
Burykin, Anton; Mariani, Sara; Henriques, Teresa et al. (2015) Remembrance of time series past: simple chromatic method for visualizing trends in biomedical signals. Physiol Meas 36:N95-102
Thomas, Robert Joseph; Mietus, Joseph E; Peng, Chung-Kang et al. (2014) Relationship between delta power and the electrocardiogram-derived cardiopulmonary spectrogram: possible implications for assessing the effectiveness of sleep. Sleep Med 15:125-31
Giladi, Nir; Horak, Fay B; Hausdorff, Jeffrey M (2013) Classification of gait disturbances: distinguishing between continuous and episodic changes. Mov Disord 28:1469-73
Maidan, Inbal; Plotnik, Meir; Mirelman, Anat et al. (2010) Heart rate changes during freezing of gait in patients with Parkinson's disease. Mov Disord 25:2346-54
Ivanov, Plamen Ch; Ma, Qianli D Y; Bartsch, Ronny P et al. (2009) Levels of complexity in scale-invariant neural signals. Phys Rev E Stat Nonlin Soft Matter Phys 79:041920
Herman, Talia; Inbar-Borovsky, Noit; Brozgol, Marina et al. (2009) The Dynamic Gait Index in healthy older adults: the role of stair climbing, fear of falling and gender. Gait Posture 29:237-41
Plotnik, M; Giladi, N; Hausdorff, J M (2009) Bilateral coordination of gait and Parkinson's disease: the effects of dual tasking. J Neurol Neurosurg Psychiatry 80:347-50
Hausdorff, Jeffrey M (2009) Gait dynamics in Parkinson's disease: common and distinct behavior among stride length, gait variability, and fractal-like scaling. Chaos 19:026113
Celi, Leo Anthony; Hinske, L Christian; Alterovitz, Gil et al. (2008) An artificial intelligence tool to predict fluid requirement in the intensive care unit: a proof-of-concept study. Crit Care 12:R151

Showing the most recent 10 out of 109 publications