At imec, Body Area Networks
Mental stress monitoring can help to prevent stress-related problems and the advent of chronic diseases. Aim of the thesis is to investigate data analysis frameworks for personalized stress detection models.
Mental stress monitoring can help to prevent stress-related problems and the advent of chronic diseases. Offices and working environments are good examples of places where stress often arises. Wearable devices able to gather physiological signals represent nowadays the most suitable technology for continuous and unobtrusive stress monitoring. At Holst Centre, a data analysis architecture and related stress detection algorithms have been developed with promising results for the detection of stress levels.
The aim of this thesis is further investigate data analysis frameworks for personalized stress detection models. The candidate will apply adaptive Machine Learning techniques and Context-Awareness methodologies for modelling stress level of the users, on the basis of stress models previously created.
The successful candidate has knowledge of Machine Learning and/or Data Mining and is fluent in at least one between MATLAB/Python and Java. Knowledge of Android programming in highly valuable.
Biomedical Engineering / Computer Science
Supervision and info
Ms Sandra Maas, Management Assistant Human Resources.
Telephone number: +31 (0)40 40 20 500