MDi: Acquisition, analysis and data visualization system in healthcare

Federico A. Bellini; Juan G. Gutierrez-Zorrilla; Luis E. Anza; Enrique D. Ferreira; Lee G. Deneault; Gabriel Vanerio

doi:10.1109/URUCON.2017.8171879

MDi: Acquisition, analysis and data visualization system in healthcare

Federico A. Bellini
, Juan G. Gutierrez-Zorrilla
, Luis E. Anza
, Enrique D. Ferreira
, Lee G. Deneault
, Gabriel Vanerio

Department of Engineering

Universidad Católica del Uruguay
British Hospital Montevideo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

This work describes an IoT solution that was designed, developed and implemented to acquire time-series, physiological data, simultaneously from different legacy medical device sources such as the communications ports of a commonly used patient monitoring system and specialized sensors. Data acquired can be further processed to observe anomalies and trends. A communications platform was also implemented for remote data visualization. A prototype of this system was then successfully deployed to collect, analyze, and visualize physiological data from patients undergoing 'Tilt Table Testing' at the British Hospital in Montevideo, Uruguay, South America.

Original language	English
Title of host publication	2017 IEEE URUCON, URUCON 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Number of pages	4
ISBN (Electronic)	9781538633977
DOIs	https://doi.org/10.1109/URUCON.2017.8171879
State	Published - 8 Dec 2017
Event	2017 IEEE URUCON, URUCON 2017 - Montevideo, Uruguay Duration: 23 Oct 2017 → 25 Oct 2017

Publication series

Name	2017 IEEE URUCON, URUCON 2017
Volume	2017-December

Conference

Conference	2017 IEEE URUCON, URUCON 2017
Country/Territory	Uruguay
City	Montevideo
Period	23/10/17 → 25/10/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Tilt Table Test
alarms
bioengineering
healthcare
medical device interconnectivity
patient monitoring systems
sensors

Access to Document

10.1109/URUCON.2017.8171879

Cite this

Bellini, F. A., Gutierrez-Zorrilla, J. G., Anza, L. E., Ferreira, E. D., Deneault, L. G., & Vanerio, G. (2017). MDi: Acquisition, analysis and data visualization system in healthcare. In 2017 IEEE URUCON, URUCON 2017 (pp. 1-4). (2017 IEEE URUCON, URUCON 2017; Vol. 2017-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/URUCON.2017.8171879

@inproceedings{121dd10f9d8f436296b494a6f062049a,

title = "MDi: Acquisition, analysis and data visualization system in healthcare",

abstract = "This work describes an IoT solution that was designed, developed and implemented to acquire time-series, physiological data, simultaneously from different legacy medical device sources such as the communications ports of a commonly used patient monitoring system and specialized sensors. Data acquired can be further processed to observe anomalies and trends. A communications platform was also implemented for remote data visualization. A prototype of this system was then successfully deployed to collect, analyze, and visualize physiological data from patients undergoing 'Tilt Table Testing' at the British Hospital in Montevideo, Uruguay, South America.",

keywords = "Tilt Table Test, alarms, bioengineering, healthcare, medical device interconnectivity, patient monitoring systems, sensors",

author = "Bellini, \{Federico A.\} and Gutierrez-Zorrilla, \{Juan G.\} and Anza, \{Luis E.\} and Ferreira, \{Enrique D.\} and Deneault, \{Lee G.\} and Gabriel Vanerio",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE URUCON, URUCON 2017 ; Conference date: 23-10-2017 Through 25-10-2017",

year = "2017",

month = dec,

day = "8",

doi = "10.1109/URUCON.2017.8171879",

language = "Ingl{\'e}s",

series = "2017 IEEE URUCON, URUCON 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--4",

booktitle = "2017 IEEE URUCON, URUCON 2017",

}

Bellini, FA, Gutierrez-Zorrilla, JG, Anza, LE, Ferreira, ED, Deneault, LG & Vanerio, G 2017, MDi: Acquisition, analysis and data visualization system in healthcare. in 2017 IEEE URUCON, URUCON 2017. 2017 IEEE URUCON, URUCON 2017, vol. 2017-December, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 2017 IEEE URUCON, URUCON 2017, Montevideo, Uruguay, 23/10/17. https://doi.org/10.1109/URUCON.2017.8171879

MDi: Acquisition, analysis and data visualization system in healthcare. / Bellini, Federico A.; Gutierrez-Zorrilla, Juan G.; Anza, Luis E. et al.
2017 IEEE URUCON, URUCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-4 (2017 IEEE URUCON, URUCON 2017; Vol. 2017-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Bellini, Federico A.

AU - Gutierrez-Zorrilla, Juan G.

AU - Anza, Luis E.

AU - Ferreira, Enrique D.

AU - Deneault, Lee G.

AU - Vanerio, Gabriel

PY - 2017/12/8

Y1 - 2017/12/8

N2 - This work describes an IoT solution that was designed, developed and implemented to acquire time-series, physiological data, simultaneously from different legacy medical device sources such as the communications ports of a commonly used patient monitoring system and specialized sensors. Data acquired can be further processed to observe anomalies and trends. A communications platform was also implemented for remote data visualization. A prototype of this system was then successfully deployed to collect, analyze, and visualize physiological data from patients undergoing 'Tilt Table Testing' at the British Hospital in Montevideo, Uruguay, South America.

AB - This work describes an IoT solution that was designed, developed and implemented to acquire time-series, physiological data, simultaneously from different legacy medical device sources such as the communications ports of a commonly used patient monitoring system and specialized sensors. Data acquired can be further processed to observe anomalies and trends. A communications platform was also implemented for remote data visualization. A prototype of this system was then successfully deployed to collect, analyze, and visualize physiological data from patients undergoing 'Tilt Table Testing' at the British Hospital in Montevideo, Uruguay, South America.

KW - Tilt Table Test

KW - alarms

KW - bioengineering

KW - healthcare

KW - medical device interconnectivity

KW - patient monitoring systems

KW - sensors

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DO - 10.1109/URUCON.2017.8171879

M3 - Contribución a la conferencia

AN - SCOPUS:85046887816

T3 - 2017 IEEE URUCON, URUCON 2017

SP - 1

EP - 4

BT - 2017 IEEE URUCON, URUCON 2017

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 23 October 2017 through 25 October 2017

ER -

MDi: Acquisition, analysis and data visualization system in healthcare

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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