Basic principles of digital biosignal processing. Time-domain and frequency-domain methods, cross-correlation, spectral analysis, convolution. Design and properties of analog and digital filters. Discrete time biosignals. Discrete time Fourier transform. Fast Fourier transform. Time-frequency analysis and wavelet transform. Pattern recognition and neural networks. Applications in ECG, EEG and EMG. Laboratory exercises using MatLab.
The objective of this course is to familiarize students with the concepts of digital biosignals, biosignal processing and analysis, as well as to provide theoretical and practical knowledge on methods and tools used for developing digital signal processing and analysis systems with applications in biomedicine. The course has both theoretical and practical aspects. The students have the opportunity to learn how to implement the theoretical notions to which they are introduced, and many examples with the use of system modelling / programming languages, such as MATLAB.
Upon successful completion of this course, students should be able to: