Specializations

First year courses Sensing and stimulation

The first-year courses of the master track MSS aim for the students to reach an advanced level in clinically relevant technology, related to the acquisition, processing and interpretation of medical signals. There is also an increasing focus on therapies to interact with (patho-)physiological processes (actuation) like neural (deep brain) stimulation.

Besides these courses, which are described in detail below, students are trained in clinical skills, work on two cases and study two optional courses of their own choice. 

Interpretation of biomedical sensing requires thorough knowledge of relevant (patho)physiology. The course “Circulation and Ventilation” integrates the knowledge of the physiology of the cardiovascular and respiratory system which have been studied separately in the bachelor programme, and the systems' approach from technological courses. This knowledge is used to understand the deregulated physiological processes in Intensive Care situations, and how these processes can be monitored and managed using technological means, for example mechanical ventilation. The students have sessions on the human patient simulator, study scientific articles about relevant physiology background and about monitoring and managing critical body functions.

The course Biological Control Systems concerns the analysis of body functions from a dynamic systems point of view. The course involves theory regarding linear and nonlinear dynamics and control, and the analysis of dynamic systems with computational tools like Matlab. Students will apply theory and tools in the dynamic analysis of physiological functions during a project.

Measurements of medical signals result in huge amounts of data. In the course Data Sciencestudents learn skills needed for data analysis. The course focuses on data preparation and visualization and on data mining; discovering patterns in large data sets involving methods from artificial intelligence, machine learning, statistics, and database systems.

Sensing includes the measurement of various biomedical signals. The course Biomedical Signal Acquisition discusses the basic processes relevant for reliable recording of biomedical signals with electrical, chemical or physical sensors. Students learn various fundamental operational principles of sensing related to biomedical applications, can identify the preferred type of sensor for a certain biomedical signal and know the do's and don'ts of the first signal processing stage.

Measurement results do not necessarily provide clinically useful information because biomedical signals often have stochastic characteristics and may change significantly during short periods of time (e.g. EEG, ECG and EMG). Using these signals for clinical research or decision making therefore requires understanding and implementation of advanced signal analysis techniques. Advanced Techniques for Signal Acquisition focuses on several advanced techniques for the analysis of biomedical signals like artefact removal and parameter estimation algorithms.

Dynamic Behaviour of Neural Networks focuses on the mathematical and biophysical principles relevant for a more fundamental understanding of neural dynamics, including the relevance of brain rhythms and their recordings (EEG). Both physiological and pathological conditions (stroke, coma, epilepsy, Parkinson’s disease) will be treated. During the course, students will apply the mathematical and biophysical tools to a ‘real-world’ clinical problem.

Each semester has two clinical skills courses: “Injections, punctures and catherizations” and “Surgical skills” in the first and “Advanced life support” and “Endoscopic skills” in the second semester. The students learn to perform the clinical skills in a simulated environment (level 3).

One optional subject is included in each semester. Students can freely choose from all master courses on offer at the University of Twente or other universities. Also self-study topics are possible.

In the clinical case, one in each semester, students apply and integrate the technological and technical-medical expertise from the other courses. These cases are real cases from the clinic and are presented and (co-)assessed by clinicians.

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