Syllabus Information

1. General information

In the subject Biomedical Signal Processing, students will understand the electrical origins of bioelectrical signals and the relationship of the different types of signals on the surface of the body (ECG, EEG, EP, EMG). This subject presents signal processing techniques for both detection and estimation in each application domain, always with clinical objectives in mind. IT should lead the student to know a range of biomedical signal processing techniques, and be able to use them to obtain clinical information from the signals, taking into account the particularities of each case and type of signal, as well as the possibilities and limitations of these techniques. Consequently, the overall objective of the subject is that the student understands and knows how to use a set of signal processing tools to extract clinically useful information from different types of biomedical signals.  

These approaches and goals are aligned with some of the Sustainable Development Goals, SDGs, of the 2030 Agenda(https://www.un.org/sustainabledevelopment/es/) and certain specific objectives: 3.d, 9.5, and 9.c.

2. Learning results

The student, in order to pass this subject, must demonstrate the following results:

1. To be able to design a biomedical signal conditioning system, taking into account the characteristics of these signals and the post-processing requirements, with the restrictions imposed by not deforming the useful information present in the signals.

2. To be able to solve problems of detection or estimation of clinical parameters of interest by optimally approaching them within the framework of the detection/estimation theory. Particularly in the area of electrocardiology, electroencephalography and electromyography.

3. To be able to interpret temporal and spatial information sources for the design of information compaction systems, either for the purpose of understanding and communication, or for the purpose of classification/monitoring and decision making regarding the underlying system (diagnosis/therapy).   

4. To be able to extrapolate concepts of signal processing to the biomedical context, interpreting spatial and temporal mixtures/separations of sources, non-uniform sampling, variant systems in the time, extraction and interpretation of static and dynamic information, etc. 

3. Syllabus

The distribution in thematic units of the theory of the subject will be as follows:

TOPIC 1. Introduction to the origin of biological signals, types and characteristics, as well as the objectives that ICTs make it possible to consider in this context.  

TOPIC 2. Electrocardiogram (ECG): Description, parameters of clinical interest, interpretation; detection of events (beats); interference cancellation; analysis of heart rate variability;  repeated signal averaging, information compression and time-varying analysis (time-frequency representations); invasive signals (electrograms), their use and singularities.

TOPIC 3. Electroencephalogram (EEG): interpretation and clinical information, frequency bands; frequency cancellation, cancellation of artifacts; spectral estimation; analysis of evoked potentials (visual, auditory, etc.).

TOPIC 4. Electromyogram (EMG): origin and interpretation; parameters of interest and optimal estimation; applications. 

TOPIC 5. Other biomedical signals: photoplethysmogram (PPG), blood pressure (BP); their interactions and physiological implications; estimates of multimodal relationships (causality, correlations, etc.) (different types of of signals) of clinical parameters.

4. Academic activities

• Lectures (40 hours), introducing the concepts, the physiological bases of each type of signal and the objectives of their study as well as the particularities or new developments of signal processing in these contexts.
• Problem solving (12 hours), which are given individually to the student, and are subsequently presented by the them in one of the regular classes. 
• Laboratory Practices(4 hours), where some of the applications presented in class will be seen in a practical way.
• Tutored work (20 hours), in which a case study will be presented, individually or preferably in a group, with real data. The student will then develop the corresponding application with a specific clinical objective.
• Assessment tests (4 hours)
• Personal study (72 hours)

5. Assessment system

The student must demonstrate achievement of the intended learning results through the following assessment activities:

• Oral presentations and discussions: During the academic year, students will prepare the presentation of specific topics or the resolution of specially selected exercises, which will later be presented orally to the whole class. The assessment of this activity represents 10% of the final grade of the subject.
• The tutored assignments represent 50% of the final grade. The grade will assess the student's analytical and critical capacity to study a problem or specific aspects of a biomedical signal processing application, making use of the theoretical and practical tools learned in the subject. In addition, the originality of the solutions, the ability to work in a group, the ability to coordinate the work and to transmit the relevant information orally and in writing will be evaluated, since the work done will be presented through a common report to the group and an oral presentation.
• Final exam: the final exam will consist of a written test that represents 40% of the final grade. The test is divided into two parts:
  theoretical-practical questions:
  Practical problems:

The student must obtain a grade of at least 4 out of 10 in the final exam to pass the subject. The student will have a global test in each one of the calls established throughout the academic year. The dates and times of the tests will be determined by the School.