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Encyclopedia of Computational Neuroscience pp 1–3Cite as

PhysioNet

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Definition

PhysioNet (http://physionet.org/) is a resource for research and education that provides free access to numerous large collections of recorded physiologic signals and time series and related open-source software for exploration and analysis of them, in support of basic, clinical, and applied research in medicine, physiology, public health, biomedical engineering and computing, and medical instrument design and evaluation. Although best known for its critical care, ECG, and cardiovascular data collections, PhysioNet curates a wide variety of data collected and contributed by neuroscientists, clinical neurologists, and researchers in allied disciplines.

Detailed Description

PhysioNet has three major components.

PhysioBankholds more than 60 open-access data collections as of 2013, containing physiologic signals and time series collected from roughly 36,000 human subjects and amounting to more than 4 TB in all. The recordings include cardiopulmonary, neural, and other...

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References

  • Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE (2000) PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23):e215–e220, Circulation Electronic Pages. http://circ.ahajournals.org/cgi/content/full/101/23/e215

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  • Moody GB (2010) The PhysioNet/computing in Cardiology Challenge 2010: mind the gap. Comput Cardiol 37:305–308

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  • Moody GB, Lehman LH (2009) Predicting acute hypotensive episodes: the 10th annual PhysioNet/computers in Cardiology Challenge. Comput Cardiol 36:541–544, PMID:20842209

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  • Moody GB, Mark RG (2001) The impact of the MIT-BIH arrhythmia database. IEEE Eng Med Biol 20(3):45–50

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  • Moody GB, Mark RG, Goldberger AL (2011) PhysioNet: physiologic signals, time series, and related open source software for basic, clinical, and applied research. In: Proceedings of the 33rd IEEE EMBS, pp 8327–8330

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  • Penzel T, McNames J, de Chazal P, Raymond B, Murray A, Moody G (2002) Systematic comparison of different algorithms for apnoea detection based on electrocardiographic recordings. Med Biol Eng Comput 40:402–407

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  • Silva I, Moody GB, Scott DJ, Celi LA, Mark RG (2012) Predicting in hospital mortality of patients in ICU: the PhysioNet/computing in Cardiology Challenge 2012. Comput Cardiol 39:245–248

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  • Silva I, Behar J, Sanemi R, Zhu T, Oster J, Clifford GD, Moody GB (2013) Noninvasive fetal ECG: the PhysioNet/computing in Cardiology Challenge 2013. Comput Cardiol 40:149–152

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Author information

Authors and Affiliations

  1. Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Room E25-505A, 77 Massachusetts Ave., Cambridge, MA, 20139, USA

    George B. Moody

Authors
  1. George B. Moody
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Corresponding author

Correspondence to George B. Moody .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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© 2014 Springer Science+Business Media New York

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Moody, G.B. (2014). PhysioNet. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_496-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_496-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

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