Enhancements for a Robust Fuzzy Detection of Stress

Improving psychologically disabled people's life quality and integration in society is strongly linked with providing them higher levels of autonomy. Occasionally, these people suffer from emotional blockages produced by situations that can be overwhelming for them. Thus, detecting whether the person is entering a mental blockage produced by stress can facilitate to mitigate the symptoms of that blockage. This work presents different enhancements and variations for an existing fuzzy logic stress detection system based on monitoring different physiological signals (heart rate and galvanic skin response). It proposes a method based on wavelet processing to improve the detection of R peaks of electrocardiograms. It also proposes to decompose the galvanic response signal into two components: the average value and the variations.