Authors:
Jeferson Cerqueira Dias
;
Jônatas Cerqueira Dias
;
Marcelo Barbosa
;
Diolino José Santos Filho
;
Fabrício Junqueira
;
Paulo Eigi Miyagi
and
Jose Roberto Cardoso
Affiliation:
University of São Paulo - USP, Prof. Luciano Gualberto Avenue, 380, São Paulo, Brazil , Department of Mechatronics Engineering and Mechanic Systems, USP, São Paulo and Brazil
Keyword(s):
Intelligent Behavior, Test Bench, Ventricular Assist Device, Reliability, In Vitro Test.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
The abstract The Ventricular Assist Device (VAD) is a mechatronic device used to treat patients with heart failure who are able to use them in short- and long-term strategies. However, with increasing population longevity, long-term use has been intensified. Thus, the development of resources that improve the robustness and reliability of these devices is justified. This work proposes an in vitro test bench with intelligent behaviour that through a systematic of protocols for the collection, treatment and monitoring of reliability data, coming from standard curves of monitored variables, such as: flow, pressure, vibration, rotation, density, viscosity and temperature, provides a decision support system with user friendly interface for verification, validation and certification of VAD. The proposed method is descriptive of an in vitro test bed model for VAD that considers the use of Petri net for validation of the dynamic behaviour in front of the variables and a decision support syst
em based on big data analytics technology with extraction of dada, which subsidizes intelligent behaviour. The proposed model is consistent with the bibliographic base and its validation. The Petri net allows confirming its application in the decision making, with intelligent behaviour, from the data mining.
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