BMT-52606 Processing of Biosignals, 5 cr
Basics of signal processing is a pre-requisite for this course.
Milla Jauhiainen, Julia Pietilä
||This course is organized according to flipped learning principles. The students are expected to complete independent studying and exercises before the contact sessions. The contact sessions ("lectures") are based on doing group exercises and discussions to deepen the knowledge from independent studies. Computer assignments are done independently, but help is available during the exercise sessions.
Course grade is based on the overall points from the following components:
50 % of the points:
- independent studies before the lectures
- participation to contact sessions
50% of the points:
- points from computer assignments
- points from final exam
This course provides the basics of applying signal processing methods on biosignals of physiological or behavioural origin. Student is assumed to have basic signal processing method knowledge and basic skills for using Matlab prior the course. After this course, the student can: - Describe and evaluate the basic properties and principles of biosignals and their measurements - Analyze examples and reasons for biosignal artefacts and missing data - Understand and evaluate different options for linear filtering of biosignals - Understand and evaluate the methods of spectral analysis and its applications in biosignal processing - Understand the statistical modelling of biosignals and classification problems - Understand the properties of performance estimations and the principles of hypothesis testing - Apply basic signal processing methods to real biosignals with MATLAB, visualize the results and analyze them critically Learning outcomes are described for grade 3.
|1.||Types and origins of physiological and biological signals, and their basic properties. Basics of data acquisition, sampling, and filtering related to biosignals.||Artefacts and missing data in biosignals.||Insights in physiological and biological signal generators.|
|2.||Filtering of biosignals. Linear filtering, filter design for biosignals.||Non-linear filtering, median filtering, adaptive filtering.|
|3.||Spectral analysis and its applications in biosignals.||Autoregressive spectral estimation.||Time-frequency analysis.|
|4.||Statistical modelling of biological data. Classification problem.||Clustering, regression analysis.|
|5.||Performance estimation, hypothesis testing.||Statistical methods in hypothesis testing and performance estimation.|
|6.||Computer exercises with Matlab: applying signal processing and analysis methods in real biosignals (incl. EEG, ECG).||Designing and implementing own algorithms for biosignal processing in Matlab.|
Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi
Exercises 20%, exam 80%. There will be 4 Matlab exercises. The final grade of the course is determined based on the assessment of all part of the course. The weighting factor of each part is given at the beginning of the course.
Numerical evaluation scale (0-5)
|Book||Biomedical Signal Analysis, 2nd edition||Rangaraj M. Rangayyan||The book can be found here and accessed from TUT network http://onlinelibrary.wiley.com/book/10.1002/9781119068129||No|
|Lecture slides||Lceture notes on Processing of Biosignals||Lecturer||Lecture notes + selected extra materials.||Yes|
|SGN-11000 Signaalinkäsittelyn perusteet||Mandatory||1|
|SGN-11007 Introduction to Signal Processing||Mandatory||1|
1 . Basic course in signal processing is needed
Basic skills in digital signal processing and in using Matlab are required.
|BMT-52606 Processing of Biosignals, 5 cr||SGN-52606 Processing of Biosignals, 5 cr|