Literature DB >> 30627871

A review of big data applications of physiological signal data.

Christina Orphanidou1.   

Abstract

The proliferation of smart physiological signal monitoring sensors, combined with the advancement of telemetry and intelligent communication systems, has led to an explosion in healthcare data in the past few years. Additionally, access to cheaper and more effective power and storage mechanisms has significantly increased the availability of healthcare data for the development of big data applications. Big data applications in healthcare are concerned with the analysis of datasets which are too big, too fast, and too complex for healthcare providers to process and interpret with existing tools. The driver for the development of such systems is the continuing effort in making healthcare services more efficient and sustainable. In this paper, we provide a review of current big data applications which utilize physiological waveforms or derived measurements in order to provide medical decision support, often in real time, in the clinical and home environment. We focus mainly on systems developed for continuous patient monitoring in critical care and discuss the challenges that need to be overcome such that these systems can be incorporated into clinical practice. Once these challenges are overcome, big data systems have the potential to transform healthcare management in the hospital of the future.

Entities:  

Keywords:  Big data; Healthcare data; Medical decision support; Physiological signal data; Smart sensors

Year:  2019        PMID: 30627871      PMCID: PMC6381367          DOI: 10.1007/s12551-018-0495-3

Source DB:  PubMed          Journal:  Biophys Rev        ISSN: 1867-2450


  9 in total

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Authors:  Adam Goldberg; Joshua W K Ho
Journal:  Biophys Rev       Date:  2020-07-14

2.  Big data: the elements of good questions, open data, and powerful software.

Authors:  Joshua W K Ho; Eleni Giannoulatou
Journal:  Biophys Rev       Date:  2019-01-25

Review 3.  Neurocritical Care: Bench to Bedside (Eds. Claude Hemphill, Michael James) Integrating and Using Big Data in Neurocritical Care.

Authors:  Brandon Foreman
Journal:  Neurotherapeutics       Date:  2020-04       Impact factor: 7.620

4.  Merging RFID and Blockchain Technologies to Accelerate Big Data Medical Research Based on Physiological Signals.

Authors:  Xiuqing Chen; Hong Zhu; Deqin Geng; Wei Liu; Rui Yang; Shoudao Li
Journal:  J Healthc Eng       Date:  2020-04-14       Impact factor: 2.682

5.  Forecasting adverse surgical events using self-supervised transfer learning for physiological signals.

Authors:  Hugh Chen; Scott M Lundberg; Gabriel Erion; Jerry H Kim; Su-In Lee
Journal:  NPJ Digit Med       Date:  2021-12-08

Review 6.  Robustness of electrocardiogram signal quality indices.

Authors:  Saifur Rahman; Chandan Karmakar; Iynkaran Natgunanathan; John Yearwood; Marimuthu Palaniswami
Journal:  J R Soc Interface       Date:  2022-04-13       Impact factor: 4.118

7.  Enabling Timely Medical Intervention by Exploring Health-Related Multivariate Time Series with a Hybrid Attentive Model.

Authors:  Jia Xie; Zhu Wang; Zhiwen Yu; Bin Guo
Journal:  Sensors (Basel)       Date:  2022-08-15       Impact factor: 3.847

8.  Consilience of methods for phylogenetic analysis of variance.

Authors:  Dean C Adams; Michael L Collyer
Journal:  Evolution       Date:  2022-05-19       Impact factor: 4.171

9.  The use of data science to analyse physiology of oxygen delivery in the extracorporeal circulation.

Authors:  Marceli Lukaszewski; Rafal Lukaszewski; Kinga Kosiorowska; Marek Jasinski
Journal:  BMC Cardiovasc Disord       Date:  2019-12-13       Impact factor: 2.298

  9 in total

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