| CODE | CBC5102 | |||||||||
| TITLE | Advanced Signal Processing for Physiological Measurement | |||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | |||||||||
| MQF LEVEL | 7 | |||||||||
| ECTS CREDITS | 5 | |||||||||
| DEPARTMENT | Centre for Biomedical Cybernetics | |||||||||
| DESCRIPTION | In this study-unit the details of physiological signal acquisition modalities will be presented to provide the students with a solid understanding of the underlying nature and characteristics of the acquired signals. The theory behind a range of advanced signal processing methods applied to these signals will be provided, together with insight on the use of these methods in practical clinical applications. The students will also acquire the necessary programming skills to implement and apply advanced signal processing techniques on physiological data. Study-Unit Aims: - The study-unit aims to provide the students with the knowledge and skills in advanced physiological signal processing; - The study-unit aims to provide the students with specific clinical applications of physiological signal processing methods, specifically: a) sleep analysis (ECG, EEG, respiratory rate, pulse oximetry); b) heart activity monitoring (ECG, pulse oximetry). - The study-unit aims to provide students with the programming skills that are necessary to implement and apply advanced signal processing methods for clinical applications using MATLAB. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Describe and apply a range of advanced signal processing methods for physiological signal analysis and processing including: a) filtering for artifact removal; b) signal decomposition methods (e.g. PCA); c) pattern classification (e.g. LDA). - Describe the relevance of these physiological signal acquisition and processing methods for the following clinical applications: a) sleep analysis (using ECG, EEG, respiratory rate, pulse oximetry); b) diagnosis of abnormal heart conditions (using ECG, pulse oximetry). 2. Skills: By the end of the study-unit the student will be able to: - Identify suitable signal analysis and processing techniques for tackling problems presented when working with physiological signal acquisition modalities; - Apply advanced mathematical and analytical skills for the analysis and processing of biomedical signals; - Apply programming skills to analyse, process and visualise biomedical signals (in MATLAB). Main Readings: - Rangayyan, R. M. (2011). Biomedical Signal Analysis (2nd ed.). Wiley. - Proakis, J. G., & Manolakis, D. G. Digital Signal Processing, Principles, Algorithms and Applications (3rd ed.). Prentice-Hall. |
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| STUDY-UNIT TYPE | Lecture and Tutorial | |||||||||
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years. |
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