Universitat Internacional de Catalunya

Signals and Systems Theory

Signals and Systems Theory
6
12489
2
Second semester
OB
TECHNOLOGY TRAINING
TECHNOLOGY
Main language of instruction: Spanish

Other languages of instruction: Catalan, English

Teaching staff


A face-to-face meeting can be arranged with the teacher by writing to his email.

Introduction

Our bodies constantly communicate information about our health. This information can be captured through physiological instruments that measure heart rate, blood pressure, oxygen saturation levels, blood glucose, nerve conduction, brain activity, etc. Traditionally, these measurements are taken at specific times and recorded in the patient's medical record. Doctors actually see less than one percent of these values as they go on their rounds, and treatment decisions are made based on these isolated readings.
Biomedical signal processing involves analyzing these measurements to provide useful information on which clinicians can make decisions. Engineers are discovering new ways to process these signals using a variety of mathematical formulas and algorithms. Working with traditional bio-measurement tools, signals can be calculated by software to provide clinicians with real-time data and increased insights to aid in clinical evaluations. By using more sophisticated means to analyze what our bodies are saying, we can potentially determine a patient's health status through more non-invasive measures.

Pre-course requirements

Algebra, Calculus, Fundamentals and Electronic Systems, Biomedical Instrumentation

Objectives

The specific objectives are:

  • Know and classify biomedical signals according to their nature.
  • To know software tools that allow to mathematically process biomedical signals.
  • Have the ability to manipulate signals through filters in discrete time.
  • Understand the relationships of the temporal and frequency domain, and be able to extract relevant information from the biomedical signals in both domains.
  • Design simple digital filters and apply basic techniques for the reduction of artifacts in biomedical signals.
  • Know standard diagnostic algorithms to process mathematically. biomedical signals for clinical application.

Competencies

  • CB1 - Students must demonstrate that they have and understand knowledge in an area of study based on general secondary education. This knowledge should be of a level that, although based on advanced textbooks, also includes some of the cutting-edge elements from their field of study.
  • CB2 - Students must know how to apply their knowledge to their work or vocation in a professional way and have the competences that are demonstrated through the creation and defence of arguments and the resolution of problems within their field of study.
  • CB3 - Students must have the ability to bring together and interpret significant data (normally within their area of study) and to issue judgements that include a reflection on important issues that are social, scientific or ethical in nature.
  • CB4 - Students can transmit information, ideas, problems and solutions to specialist and non-specialist audiences.
  • CB5 - Students have developed the necessary learning skills to undertake subsequent studies with a high degree of autonomy.
  • CE1 - To solve the maths problems that arise in the field of Bioengineering. The ability to apply knowledge of geometry, calculate integrals, use numerical methods and achieve optimisation.
  • CE12 - To undertake a professional project in the field of Bioengineering-specific technologies in which knowledge acquired through teaching is synthesised and incorporated.
  • CE13 - To identify, understand and use the principles behind electronics, sensors, air conditioners and systems that acquire biomedical signals
  • CE15 - The ability to undertake a project through the use of data sources, the application of methodologies, research techniques and tools specific to Bioengineering, give a presentation and publicly defend it to a specialist audience in a way that demonstrates the acquisition of the competences and knowledge that are specific to this degree programme.
  • CE16 - To apply specific Bioengineering terminology both verbally and in writing in a foreign language.
  • CE17 - To be able to identify the engineering concepts that can be applied in the fields of biology and health.
  • CE21 - The ability to understand and apply biotechnological methodologies and tools to research, as well as to the development and production of products and services.
  • CE3 - To apply fundamental knowledge on using and programming computers, operating systems, databases and IT programs to the field of Bioengineering.
  • CE8 - To hold a dialogue based on critical thinking on ideas connected to the main dimensions of the human being
  • CG10 - To know how to work in a multilingual and multidisciplinary environment.
  • CG2 - To promote the values that are specific to a peaceful culture, thus contributing to democratic coexistence, respect for human rights and fundamental principles such as equality and non-discrimination.
  • CG3 - To be able to learn new methods and theories and be versatile so as to adapt to new situations.
  • CG4 - To resolve problems based on initiative, be good at decision-making, creativity, critical reasoning and communication, as well as the transmission of knowledge, skills and prowess in the field of Bioengineering
  • CG5 - To undertake calculations, valuations, appraisals, expert reports, studies, reports, work plans and other similar tasks.
  • CG6 - To apply the necessary legislation when exercising this profession.
  • CG7 - To analyse and evaluate the social and environmental impact of technical solutions
  • CG8 - To apply quality principles and methods.
  • CT2 - The ability to link welfare with globalisation and sustainability; to acquire the ability to use skills, technology, the economy and sustainability in a balanced and compatible manner.
  • CT3 - To know how to communicate learning results to other people both verbally and in writing, and well as thought processes and decision-making; to participate in debates in each particular specialist areas.
  • CT4 - To be able to work as a member of an interdisciplinary team, whether as a member or by management tasks, with the aim of contributing to undertaking projects based on pragmatism and a feeling of responsibility, taking on commitment while bearing the resources available in mind.
  • CT5 - To use information sources in a reliable manner. To manage the acquisition, structuring, analysis and visualisation of data and information in your specialist area and critically evaluate the results of this management.
  • CT6 - To detect gaps in your own knowledge and overcome this through critical reflection and choosing better actions to broaden your knowledge.
  • CT7 - To be fluent in a third language, usually English, with a suitable verbal and written level that is in line with graduate requirements.

Learning outcomes

Once the course is finished, the student will be able to:

  • Know the basic signals from biological systems.
  • Acquire quality biomedical signals.
  • Understand the basic principles of biomedical signal processing.
  • Process signals with software tools.

Syllabus

Chapter 0. Introduction. Analog and digital signals.

Practical examples: Recording of analog signals from electronic transducers and visualization using an oscilloscope.

 

Chapter 1. The sinusoidal signal

Practical examples: Graphic representation of sinusoidal signals by computer. Variable frequency sinusoidal signal generation for audiometry applications. Mathematical modeling of EMG signals with sinusoidal signals.

 

Chapter 2. Sampling of analog signals

Practical examples: acquisition of a signal. Use of educational signal acquisition systems (Biopac, Labtutor, etc.). Study of the effect of the sampling theorem (Nyquist) in the acquisition of biomedical signals.

 

Chapter 3. Convolution and correlation

Practical examples: Computer graphic representation and calculation of correlation, application of normalized cross-correlation for detection of similarity between signals, detection of similar EMG signals with correlation in a configuration of electrode arrays.

 

Chapter 4. The Fourier Transform

Practical examples: Graphic representation and calculation of the fast Fourier transform (FFT) by computer, acquisition of the ECG signal with educational signal acquisition systems (Biopac, Labtutor, etc.) and obtaining the frequency spectrum.

 

Chapter 5. Digital filters

Practical examples: Calculation of the transfer function of digital filters using a computer, computer application of the convolution theorem, computer application of filtering the noise of the electrical network and its harmonics, digital filtering of the ECG signal acquired in the laboratory. Acquisition and filtering of the EEG signal with educational signal acquisition systems (Biopac, Labtutor, etc.) and obtaining the different frequency bands by filtering.

 

Chapter 6. Time-frequency representation, spectrogram

Practical examples: Graphic representation and calculation of the spectrogram of heart sounds (Phonocardiogram). Graphic representation and calculation of the spectrogram of the ECG signal acquired by the laboratory using different parametric and non-parametric methods.

 

Chapter 7. The Wavelet transform

Practical examples: Computer calculation of the Wavelet transform in the laboratory acquired ECG signal for the automatic detection of QRS events.

Teaching and learning activities

In person



TRAINING ACTIVITY METHODOLOGY COMPETENCES
Cooperative learning plays a significant role in the Bachelor’s degree in Bioengineering, its approach is based on organising activities inside the classroom so they become both a social and an academic learning experience. This type of learning depends on an exchange of information between students, who are motivated both to achieve their own learning and to increase the achievements of others. This activity covers practicums undertaken in a laboratory environment. Lectures are the setting for: learning and managing the terminology and language structures related to each scientific field. Practicing and developing oral and written communication skills. And learning how to analyse the bibliography and literature on Bioengineering. Using guidelines to identify and understand the main ideas during lectures. This academic activity has been an essential tool in education since it first began and should have a significant presence within the framework of this degree programme. Case studies are a learning technique in which the subject is faced with a description of a specific situation that involves a problem, that must be understood, evaluated and resolved by a group of people through a process of debate. Case studies will generally be undertaken through group work, which promotes student participation, thus developing their critical thinking skills. It also prepares students for decision-making, teaching them to defend their arguments and contrast them with opinions from others in the group. An activity for outside the classroom. This activity means students can allow their knowledge to settle and rest, which is always necessary before beginning a new task. The professor sets out exercises and problems, helps students to progress in terms of the engineering process the design involves, and guides the student, thus partial goals are achieved that facilitate the incorporation of the theoretical knowledge acquired. An activity for outside the classroom. During this activity, students complete exercises autonomously, without the presence of a lecturer/professor. At this stage many questions always arise, but since they cannot be asked immediately then the student has to make more effort to understand them Student activities guided by the lecturer/professor will be undertaken on-site and the student’s evolution will be monitored consistently. Practical classes allow students to interact at first hand with the tools they will need to use in their work. In small groups or individually practical demonstrations will be carried out based on the theoretical knowledge acquired during the theory classes. In theory classes the fundamental and scientific knowledge that forms the basis of the knowledge and rigour that engineering studies require must be established. Individual work, involving study, the search for information, data processing and the internalisation of knowledge will allow students to consolidate their learning. CB1 CB2 CB3 CB4 CB5 CE1 CE13 CE15 CE16 CE17 CE3 CG10 CG2 CG3 CG4 CG5 CG6 CG7 CT3 CT4 CT5 CT6 CT7

Evaluation systems and criteria

In person



Fully face-to-face mode in the classroom

The final grade for the course will be obtained as;
Note = 0.3 Nef + 0.3 Nlab + 0.2 Ntreb + 0.2 Nparc 

where

Nparc: Partial exam grade

Nef: Final exam grade

Nlab: Laboratory practice note

Ntreb: Note works of the subject

 

To qualify for the apt it is essential to carry out the subject's laboratory practices.

 

Important considerations:

Plagiarism, copying or any other action that can be considered cheating will result in a zero in that evaluation section. Taking it in the exams will mean the immediate failure of the subject.
In the second call, the qualification of "Matriculation of Honor" will not be able to be obtained, reason why the maximum qualification will be of "Excellent".
Changes in the calendar, exam dates or in the evaluation system will not be accepted.
Exchange students (Erasmus and others) or repeaters will be subject to the same conditions as the rest of the students.

Bibliography and resources

[1] Proakis, John G ; Manolakis, Dimitris G. Digital Signal Processing. 4th ed. Madrid: Prentice-Hall, 2006. ISBN-10 : 0131873741.

[2] John Enderle, Joseph Bronzino. 2011. Introduction to Biomedical Engineering, 3 ed. ISBN : 978-0123749796.

[3] Alan V. Oppenheim, Alan S. Willsky. Signals And Systems. Pearson. 2nd Edition. 2017. ISBN-10 : 9332550239.