Biossinais e Biossensores

Code:

MEB04

Sigla:

Level:

Áreas Científicas
Classificação	Área Científica
OFICIAL	Controlo de Processos
OFICIAL	Electronics and Telecommunications

Ocorrência: 2022/2023 - 1S

Ativa?	Yes
Unidade Responsável:	Departamento de Engenharia Eletrotécnica
Curso/CE Responsável:

Ciclos de Estudo/Cursos

Sigla	Nº de Estudantes	Plano de Estudos	Anos Curriculares	Créditos UCN	Créditos ECTS	Horas de Contacto	Horas Totais
MEB	12	Plano Oficial do ano letivo 2021	1	-	6	60	162

Docência - Responsabilidades

Docente	Responsabilidade
Tito Gerardo Batoreo Amaral

Docência - Horas

Theorethical and Practical :	1,00
Practical and Laboratory:	3,00

Type	Docente	Turmas	Horas
Theorethical and Practical	Totais	1	1,00
	Carla Maria de Almeida Amorim Carneiro		1,00
	Tito Gerardo Batoreo Amaral		1,00
Practical and Laboratory	Totais	1	3,00
	Carla Maria de Almeida Amorim Carneiro		3,00
	Rui Pedro Batoreo Amaral		3,00

A ficha foi alterada no dia 2022-10-20.

Campos alterados: Fórmula de cálculo da classificação final

Língua de trabalho

Portuguese

Objetivos

At the level of Biosensors, the course aims to make known the various types of biosensors and their operating principles. Understand the ways of transduction of a biosensor and its specific applications, aiming to carry out a biosensor project. Within the scope of Biosignals, the objective is to present some algorithms for segmentation, information extraction and biosignal classification using computational tools.

Resultados de aprendizagem e competências

- Know the fundamentals of the design, construction, operation and analysis of results obtained with biosensors;
- Describe the principles of operation and signal transduction in biosensors;
- Equate, for a given biosensor, on the most suitable biological element for the analyte under study and how to immobilize it;
- Design, build and evaluate the functioning of a biosensor;
- Know the fundamental concepts and steps associated with the acquisition, packaging, digitization, visualization and analysis of biosignals;
- Know the fundamental concepts associated with the 2D digital signal and its visualization;
- Know and know how to apply some medium and high complexity algorithms used in the extraction of information from physiological signals (2D);
- Know and know various techniques of digital signal processing in order to segment and classify biosignals.

Modo de trabalho

Presencial

Programa

Biosignals

1. Introduction to the acquisition and processing of discrete signals;
2. Fundamentals of the acquisition, visualization and analysis of biosignals;
3. The acquisition, conditioning and digitalization of signals;
4. Introduction to Digital Signal Processing of 2D signals;
5. Fundamentals of digital 2D signals and its visualization;
6. Algorithms for features extraction from physiological signals (2D);
7. Segmentation and classification of biosignals.

Biosensores
1. Introduction to biosensors;

2. The biochemical foundations of biosensors;

3. Biological imobilization methods;

4. DNA and SPR biosensors;

5. Analytical devices with Biosensor integration;

6. Biosensors Applications .

Bibliografia Obrigatória

Xueji Zhang, Huangxian Ju and Joseph Wang; Electrochemical sensors, biosensors and their biomedical applications, Elsevier/Academic Press. ISBN: 978-0-12-373738-0
Philip N. Bartlett; Bioelectrochemistry: fundamentals experimental techiques and applications. ISBN: 978-0-470-84364-2
Gonzalez, R. e Woods, R.; Digital Image Processing.. ISBN: 0-01-18175-8
Rangayan, R.; Biomedical Image Analysis. ISBN: 9781849396953
Semmlow, John L.; Biosignal and Biomedical Image Processing – Matlab-Based Applications. ISBN: 0-8247-4813-4
Ballard, Dana H. and Cristopher, M. Brown; Computer Vision, Prentice Hall, 1982

Métodos de ensino e atividades de aprendizagem

Theoretical/practical classes:
- Exposition of theoretical matters.

Laboratory classes:

- Carrying out laboratory work with the support of specific guides. In some works, a report is produced and presented. Simulation tools are used in carrying out some laboratory work.

Software

Matlab
Anaconda

Tipo de avaliação

Distributed evaluation without final exam

Componentes de Avaliação

Designation	Peso (%)
Apresentação/discussão de um trabalho científico	37,50
Trabalho laboratorial	62,50
Total:	100,00

Componentes de Ocupação

Designation	Tempo (Horas)
Estudo autónomo	102,00
Frequência das aulas	60,00
Total:	162,00

Obtenção de frequência

Continuous Evaluation
or Final Exam

Fórmula de cálculo da classificação final

The final grade of the course is calculated as follows:

NF = (0,375 x P_BiosIn + 0.125 x A_BiosIn) + (0,15 x L_BiosEn + 0,35 x S_BiosEn)

Legend:
NF - Final Grade
P_BiosIn - Evaluation grade of Biosignal Project
A_BiosIn - Evaluation grade of Biosignal Project Presentation
L_BiosEn - Evaluation grade of Biosensor laboratory work
S_BiosEn - Evaluation grade of Biosensor Seminar

Notes:
(1) There is no minimum grade in the four evaluation components;
(2) The achievement of a Final Grade greater or equal to 9.50 values (NF> = 9.50 values) allows the student to have approval in the discipline.

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