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Intelligente Signalanalyse in der Medizin


Lecturer: Prof Björn Schuller, Dr. Nicholas Cummins
Date: Lecture Mondays 10:00 - 11:30 WIWI 1003 K Tutorial Wednesdays 15:45 - 17:15 Zentrales HSZ 2106 D
Building/Room:
Students will learn the principal concepts of signal processing, signal source separation, feature extraction and information reduction exemplified by mHealth signals. They will also gain insight into machine learning principles needed for intelligent signal analysis. They will learn about different problems and solutions in the analysis of signals such as speech, audio, facial, body, gait and wearable sensors. The student will gain skills in being able to choose appropriate algorithms of signal processing and machine intelligence and experience in applying this skill set to a broad range of mhealth signal analysis problems. Students will gain competences in being to characterise, judge on the quality and suitability, and design suited algorithmic solutions for intelligent signal analysis with a focus on mHelath signals. Further they will be able to extract meaningful and relevant features and process these with modern approaches of machine intelligence.


More information:

Recommended semester: Master
Field of study: Informatik
Duration: 4 SWS
Type: V - Vorlesung
Semester: WS 2017/18