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A Cloud Computing Solution for Patient's Data Collection in Health Care Institutions.

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Abstract

Existing processes for patients' vital data collection require a great deal of labor work to collect, input and analyze the information. These processes are usually slow and error- prone, introducing a latency that prevents real-time data accessibility. This scenario restrains the clinical diagnostics and monitoring capabilities. We propose a solution to automate this process by using “sensors” attached to existing medical equipments that are inter-connected to exchange service. The proposal is based on the concepts of utility computing and wireless sensor networks. The information becomes available in the “cloud” from where it can be processed by expert systems and/or distributed to medical staff. The proof-of-concept design applies commodity computing integrated to legacy medical devices, ensuring cost- effectiveness and simple integration.
9/24/17, 9)52 AMA Cloud Computing Solution for Patient's Data Collection in Health Care Institutions - IEEE Conference Publication
Page 1 of 3http://ieeexplore.ieee.org/document/5432853/
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Carlos Oberdan Rolim ; Fernando Luiz Koch ; Carlos Becker Westphall ; Jorge Werner ; Armando Fracalossi ; Giovanni Schmitt Salvador
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Abstract:
Existing processes for patients' vital data collection require a great deal of labor work to collect, input and analyze the information. These processes
are usually slow and error-prone, introducing a latency that prevents real-time data accessibility. This scenario restrains the clinical diagnostics and
monitoring capabilities. We propose a solution to automate this process by using “sensors” attached to existing medical equipments that are inter-
connected to exchange service. The proposal is based on the concepts of utility computing and wireless sensor networks. The information becomes
available in the “cloud” from where it can be processed by expert systems and/or distributed to medical staff. The proof-of-concept design applies
commodity computing integrated to legacy medical devices, ensuring cost-effectiveness and simple integration.
Published in: eHealth, Telemedicine, and Social Medicine, 2010. ETELEMED '10. Second International Conference on
Date of Conference: 10-16 Feb. 2010
Date Added to IEEE Xplore: 18 March 2010
ISBN Information:
INSPEC Accession Number: 11191063
DOI: 10.1109/eTELEMED.2010.19
Publisher: IEEE
Conference Location: St. Maarten, Netherlands Antilles
Contents
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I. Introduction
Telemedicine allows remote diagnoses and monitoring of patients [1]. It guarantees agility, safety,
and reliability in modern health-care institutions. There are several challenges associated to
automation in this sort of environment [2], viz: heterogeneity of devices, protocols, and
programming interfaces; the requirement for flexible, impact-free deployment; the requirement for
easy to configure, easy to manage, scalable and, if possible, self-adjusting systems, and others.
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I. Introduction
II. Motivation
III. Related Works
IV. Proposal
V. Conclusions and Future Works
9/24/17, 9)52 AMA Cloud Computing Solution for Patient's Data Collection in Health Care Institutions - IEEE Conference Publication
Page 2 of 3http://ieeexplore.ieee.org/document/5432853/
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IEEE Keywords
Cloud computing, Medical services, Medical diagnostic imaging, Information analysis, Delay,
Patient monitoring, Biomedical monitoring, Biomedical equipment, Proposals, Computer networks
INSPEC: Controlled Indexing
wireless sensor networks, health care, Internet, medical computing, medical information systems,
mobile computing, telemedicine
INSPEC: Non-Controlled Indexing
wireless sensor network, cloud computing, patient data collection, health care institution, clinical
diagnostic, clinical monitoring, utility computing
Author Keywords
cloud computing, utility computing, sensor networks, telemedicine
Authors
Carlos Oberdan Rolim
Network & Manage. Lab.-LRG, Fed. Univ. of Santa Catarina,
Florianopolis, Brazil
Fernando Luiz Koch
Network & Manage. Lab.-LRG, Fed. Univ. of Santa Catarina,
Florianopolis, Brazil
Carlos Becker Westphall
Network & Manage. Lab.-LRG, Fed. Univ. of Santa Catarina,
Florianopolis, Brazil
Jorge Werner
Network & Manage. Lab.-LRG, Fed. Univ. of Santa Catarina,
Florianopolis, Brazil
Armando Fracalossi
Network & Manage. Lab.-LRG, Fed. Univ. of Santa Catarina,
Florianopolis, Brazil
Giovanni Schmitt Salvador
Network & Manage. Lab.-LRG, Fed. Univ. of Santa Catarina,
Florianopolis, Brazil
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9/24/17, 9)52 AMA Cloud Computing Solution for Patient's Data Collection in Health Care Institutions - IEEE Conference Publication
Page 3 of 3http://ieeexplore.ieee.org/document/5432853/
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