Results from personalized and portable monitoring
Konstanz, December 2017. The overall scientific goal of the collaboration between HTWG Konstanz (Prof. Dr. Seepold), Slovak University of Technology (Prof. Dr. Lehocki) and Reutlingen University (Prof. Dr. Martínez Madrid) is to detect and analyze a person's emotion with the help of a sensor network in order to support diagnostic decisions. In this project, emotion detection requires personalized analysis of a multi-dimensional set of parameters in real-time. The set of acquired parameters include different bio vital data (like ECG, EEG, skin conductivity, etc.) together with non- bio vital data (like location, movement/activity detection, activity in social media, etc.). These parameters are stored in a time-series of multidimensional matrices. Different parameters of both types (vital and non-vital) can be combined in subsets to perform pattern-based emotion recognition. For example, stress is associated with certain ECG-patterns (increased heart rate), and the recognized activity (for example running) can be used to strengthen or weaken (as in this case) the emotion recognition result.