Literature DB >> 21093093

Using "off-the-shelf" tools for terabyte-scale waveform recording in intensive care: computer system design, database description and lessons learned.

Anton Burykin1, Tyler Peck, Timothy G Buchman.   

Abstract

Until now, the creation of massive (long-term and multichannel) waveform databases in intensive care required an interdisciplinary team of clinicians, engineers and informaticians and, in most cases, also design-specific software and hardware development. Recently, several commercial software tools for waveform acquisition became available. Although commercial products and even turnkey systems are now being marketed as simple and effective, the performance of those solutions is not known. The additional expense upfront may be worthwhile if commercial software can eliminate the need for custom software and hardware systems and the associated investment in teams and development. We report the development of a computer system for long-term large-scale recording and storage of multichannel physiologic signals that was built using commercial solutions (software and hardware) and existing hospital IT infrastructure. Both numeric (1 Hz) and waveform (62.5-500 Hz) data were captured from 24 SICU bedside monitors simultaneously and stored in a file-based vital sign data bank (VSDB) during one-year period (total DB size is 4.21TB). In total, vital signs were recorded from 1,175 critically ill patients. Up to six ECG leads, all other monitored waveforms, and all monitored numeric data were recorded in most of the cases. We describe the details of building blocks of our system, provide description of three datasets exported from our VSDB and compare the contents of our VSDB with other available waveform databases. Finally, we summarize lessons learned during recording, storage, and pre-processing of physiologic signals.
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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Year:  2010        PMID: 21093093     DOI: 10.1016/j.cmpb.2010.10.004

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  5 in total

1.  Remembrance of time series past: simple chromatic method for visualizing trends in biomedical signals.

Authors:  Anton Burykin; Sara Mariani; Teresa Henriques; Tiago F Silva; William T Schnettler; Madalena D Costa; Ary L Goldberger
Journal:  Physiol Meas       Date:  2015-05-27       Impact factor: 2.833

2.  Trending autoregulatory indices during treatment for traumatic brain injury.

Authors:  Nam Kim; Alex Krasner; Colin Kosinski; Michael Wininger; Maria Qadri; Zachary Kappus; Shabbar Danish; William Craelius
Journal:  J Clin Monit Comput       Date:  2015-10-07       Impact factor: 2.502

3.  Design and implementation of a hospital wide waveform capture system.

Authors:  James M Blum; Heyon Joo; Henry Lee; Mohammed Saeed
Journal:  J Clin Monit Comput       Date:  2014-09-16       Impact factor: 2.502

Review 4.  Big Data Analytics in Healthcare.

Authors:  Ashwin Belle; Raghuram Thiagarajan; S M Reza Soroushmehr; Fatemeh Navidi; Daniel A Beard; Kayvan Najarian
Journal:  Biomed Res Int       Date:  2015-07-02       Impact factor: 3.411

Review 5.  Artificial intelligence in telemetry: what clinicians should know.

Authors:  David M Maslove; Paul W G Elbers; Gilles Clermont
Journal:  Intensive Care Med       Date:  2021-01-02       Impact factor: 17.440

  5 in total

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