Interfaces and Data Acquisition Systems

Year
0
Academic year
2022-2023
Code
02007869
Subject Area
Biomedical Engineering
Language of Instruction
Portuguese
Mode of Delivery
Face-to-face
Duration
SEMESTRIAL
ECTS Credits
6.0
Type
Elective
Level
2nd Cycle Studies - Mestrado

Recommended Prerequisites

Electronics; Signals and Systems.

Teaching Methods

- Presentation of the syllabus with support of laboratory classes, problem solving and programming examples and challenges.
- Students are encouraged to work alone and in groups.

Learning Outcomes

- Understand the global architecture of data acquisition systems.
- Identify and characterize the different tasks and functions of a data acquisition system.
- Identify the physical and technical limitations of data acquisition systems and the associated instrumentation.
- Develop the skills to use and specify data acquisition systems.
- Learn basic and intermediate concepts of sensor elements and data communication networks.
- Use data analysis tools for data processing (Matlab) in the scope of data acquisition systems.

Work Placement(s)

No

Syllabus

1. Data Acquisition Systems
Generic Architecture. Characterization and performance evaluation. Examples.

2. Transducers
Definitions, characteristics and terminology. Main types of sensors. Calibration and compensation.

3. Signal Conditioning and Multiplexing
Measurement bridges. Amplification. Operational amplifiers. Instrumentation and isolation amplifiers.

4. Noise
Noise characterization measurements. Intrinsic noise: theral, quantum, and 1/f. Extrinsic noise coupling. Methods for noise elimination. Ground loops.

5. Analog-to- Digital Conversion
Periodic sampling of signals. Nyquist sampling theorem. Quantization and non-linearity errors. Signal to Noise Ratio and Effective Number of Bits. Test and characterization of converters. Main type of converters.

6. Analysis and filtering
Properties of analog and digital signals. Analysis of the frequency spectrum. Linear systems. Autocorrelation, cross-correlation and convolution. FIR and IIR digital filters.

Head Lecturer(s)

Jorge Afonso Cardoso Landeck

Assessment Methods

Assessment
Resolution Problems: 40.0%
Exam: 60.0%

Bibliography

- Class presentations and notes
- John Bentley, Principles of Measurement, Pearson/Prentice Hall, 2005.
- Aurélio Campilho, Instrumentação Electrónica. Métodos e Técnicas de Medição, FEUP Edições, 2000.
- Maurizio Di Paolo Emilio, Data Acquisition Systems From Fundamentals to Applied Design, Springer, 2013.
- Data Acquisition Fundamentals, National Instruments, 2002.