Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
DATA: 28/04/2023
HORA: 09:00
LOCAL: Google meet
TÍTULO: A Flexible and Intelligent Capnograph based on Internet of Things and Biofeedback Technology
PALAVRAS-CHAVES: Capnography; Internet of Things; wearable; artificial intelligence; monitoring; mechanical ventilation; health care; blynk platform; MQ-135 sensor; biofeedback.
GRANDE ÁREA: Engenharias
ÁREA: Engenharia Elétrica

With the scenario of the global health crisis established by the COVID-19 pandemic,
there was a significant increase in the demand for medical services, generating serious
problems of shortage of medical equipment, such as monitoring devices by capnography and
mechanical ventilation. Although protocols and security measures have emerged to control
the chaotic situation, these criteria were insufficient to prevent deaths and an increase in the
number of patients.
To face this context, it was necessary not only to look for ways to allocate resources
(financial, inputs, and equipment) but also to discover new techniques with viable
implementation potential. Thus, there has been a significant increase in research on flexible,
low-cost sensors and modern technologies that respond to rapid production processes.
Therefore, in the meantime, the effort of researchers around the world to test and validate
flexible health equipment is notorious. And as a consequence, the emergence of a large
number of prototypes with excellent performance and performance, such as wearable and
intelligent solutions based on the Internet of Things (IoT) for capnography. These solutions
can improve and optimize the monitoring system and promote a safe, effective, and proactive
medical service. However, these systems still have many gaps that add pertinent questions
including robustness, continuous monitoring, usability, and cost-effectiveness. However, the
specificities of these points require overcoming a set of challenges that can impact the
performance and viability of the applied technique. Given this, the biggest challenge to be
faced by researchers is to find new solutions with more sophisticated and viable methods.
The research community is moving towards studies and research to discover
technologies that integrate production processes more quickly and at lower costs. Modern
and flexible technologies have great potential for implementation but have been used in a
generalized way, such as the MQ-135 gas sensor, which is a low-cost sensor, abundant in the
market and that can offer the system flexibility and speed in the process. of production.
Other impactful tools are the Internet of Things (IoT) integrated with the techniques
of the Blynk platform that can develop systems with remote management and in real-time
and the biofeedback technology that appears with a great perspective of innovation, if you
consider the use of feedback luminous. These technologies can work synergistically to
improve and optimize a device's performance. To illustrate this process, consider a respiratory
rate monitoring system (capnograph) that operates continuously, reads, analyzes the data, 

controls, and sends it to the server that stores and makes it available through a web graphic
interface or mobile App.
These points become very promising research topics in the area of capnography, and
for this reason, they are addressed in this research work. Therefore, this dissertation work is
motivated by the need to deal with the problems inherent in the monitoring system
(capnography), such as, for example, assuring the patient a fast and safe treatment.
In an attempt to solve some of these questions, this dissertation presents a case study
with the MQ-135 sensor to experiment and evaluate a technological hypothesis, considering
the device, methodology, and software for a hospital and outpatient capnograph based on
light feedback and data processing (histogram-type curve, CO2 saturation as a function of
The purpose of this proposal is to expand the use of the capnograph presented for
post-extubation pulmonary rehabilitation so that patient monitoring is a simple, calm, fast,
safe, and effective procedure. It was demonstrated from the first experiments that the
development of an intelligent and flexible capnograph presents satisfactory results for the
monitoring of biofeedback activities and excellent potential to help patients in the process of
pulmonary rehabilitation.
The results observed and verified in this work are intended to contribute to the
advancement of the state of the art on solutions for capnography through new approaches,
methodologies, and techniques to overcome the challenges that arise from the performance
of traditional models.

Interno - 1615907 - FABIO ROCHA BARBOSA
Externo ao Programa - 2009986 - GILDARIO DIAS LIMA
Presidente - 621.466.243-37 - JOEL JOSE PUGA COELHO RODRIGUES - UA
Notícia cadastrada em: 18/04/2023 16:03
SIGAA | Superintendência de Tecnologia da Informação - STI/UFPI - (86) 3215-1124 | © UFRN | 26/02/2024 11:37