Introduction to software tools for scientific computing and their use for the design of biosignal processing algorithms. Data Analysis. Data fitting, criteria for model selection and identification, LMS estimation. Interpolation. Signal analysis. FFT and harmonic analysis of biosignals. Design of FIR and IIR filters for biomedical applications, detection of waves and patterns. Spectral estimate: parametric and non-parametric methods, application to EEG and Heart Rate Variability signals. Enhancement of evoked potentials: averaging and single sweep approach. Advanced topics of biosignal processing will be exploited through specific project assignment. Project topics range from multi-variate parametric estimate, optimal filters, time-frequency transform, to non-linear analysis, synchronization and coupling. Biomedical signal and data to be analysed: Electrocardiogram (ECG) blood pressure, respiration, Elettroencephalogram (EEG) and evoked potentials, otoacustic emission, voice signals, DNA sequences.

It should be noted that this is a limited number access course. The mandatory procedure for access request is here (http://www.ccsbio.polimi.it/)

During the course students will works in small groups under the supervision of the lecturer. The groups will be asked to implement biomedical signal processing algorithms. A final project will be assigned to each group. The project, its implementation and the related results will be discussed during the oral exam.