A stress recognition system using HRV parameters and machine learning techniques

• Published in: 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) pp. 269 - 272
• Main Authors: Giannakakis, Giorgos, Marias, Kostas, Tsiknakis, Manolis
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2019
• Subjects: ECG; Electrocardiography; Feature extraction; heart rate; Heart rate variability; HRV; pairwise transformation; Reliability; Stress; stress classification; Support vector machines; Task analysis

In this study, we investigate reliable heart rate variability (HRV) parameters in order to recognize stress. An experiment protocol was established including different stressors which correspond to a range of everyday life conditions. A personalized baseline was formulated for each participant in or...