stress_ML_detector

signal processing of HR, BVP and GSR for stress detection The objective of this work is to be able to characterize different signals for the detection of stress and to be able to distinguish 3 different stages of respiration (normal, fast and slow). To achieve this, the signals of 9 patients are analyzed. Once each signal and each stage have been characterized, a characteristics matrix is constructed. Finally, this information is presented to a Machine Learning algorithm to perform the classification and detect the different stages and then proceed to the validation of the model.