# Research Resource for Complex Physiologic Signals

> **NIH NIH R01** · BETH ISRAEL DEACONESS MEDICAL CENTER · 2024 · $652,827

## Abstract

PhysioNet, established in 1999 as the NIH-sponsored Research Resource for Complex Physiologic Signals,
has attained a preeminent status among biomedical data and software resources. Its data archive was the first,
and remains the world's largest, most comprehensive and widely used repository of time-varying physiologic
signals. Its software collection supports exploration and quantitative analyses of its own and other databases
by providing a wide range of well-documented, rigorously tested open-source programs. PhysioNet's team of
researchers drive the creation and enrichment of: i) data collections that provide comprehensive, multifaceted
views of pathophysiology over long time intervals, such as the MIMIC (Medical Information Mart for Intensive
Care) Databases of critical care patients; ii) analytic methods for quantification of information encoded in
physiologic signals relevant to risk stratification and health status assessment; iii) user interfaces, reference
materials and services that add value and improve access to the resource’s data and software, and iv) unique
annual signal analysis Challenges focusing on high priority clinical problems, such as early prediction of
sepsis, detection and quantification of sleep apnea syndromes from a single lead electrocardiogram (ECG),
false alarm detection in the intensive care unit (ICU), continuous fetal ECG monitoring, paroxysmal atrial
fibrillation detection and prediction, and predicting the level of neurologic recovery from coma after cardiac
arrest. PhysioNet is a proven enabler and accelerator of innovative research by investigators with a diverse
range of interests, working on projects made possible by otherwise inaccessible data. PhysioNet's worldwide
and growing community of users include researchers, clinicians, educators, trainees, and medical instrument
and software developers. The PhysioNet enterprise was recognized with the 2016 Laufman-Greatbatch Award,
the highest honor accorded by the Association for the Advancement of Medical Instrumentation (AAMI).
PhysioNet Challenges received the 2022 "Distinguished Achievement Award for Data Reuse,” as part of the
inaugural NIH DataWorks! Prize. PhysioNet has been designated as an NIH/NIBIB sponsored data-sharing
repository. Over the next five years, we aim to: 1) magnify PhysioNet’s impact with new data and technology;
2) develop novel computational methodologies to quantify dynamical information of basic and translational
value encoded in physiologic signals, and 3) harness the research community through our international
Challenges that address key clinical problems, emphasizing the application of artificial intelligence
methodologies.

## Key facts

- **NIH application ID:** 10979705
- **Project number:** 2R01EB030362-17
- **Recipient organization:** BETH ISRAEL DEACONESS MEDICAL CENTER
- **Principal Investigator:** Ary Louis Goldberger
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $652,827
- **Award type:** 2
- **Project period:** 2007-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10979705

## Citation

> US National Institutes of Health, RePORTER application 10979705, Research Resource for Complex Physiologic Signals (2R01EB030362-17). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10979705. Licensed CC0.

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