A novel physiological feature selection method for emotional stress assessment based on emotional state transition - Li, Zhen; Xing, Yun; Pi, Yao; Jiang, Mingzhe; Zhang, Lejun (Frontiers in Neuroscience, 2023)
The connection between emotional states and physical health has attracted widespread attention. The emotional stress assessment can help healthcare professionals figure out the patient’s engagement towards the diagnostic plan and optimize the rehabilitation program as feedback. Previous studies had used the differences in physiological features between discrete emotional states to select feature subsets. However, the emotional state of the human body is continuously changing. The conventional feature selection methods ignored the dynamic process of an individual’s emotional stress in real life. Therefore, a dedicated experimental was conducted while three peripheral physiological signals, i.e., ElectroCardioGram (ECG), Galvanic Skin Resistance (GSR), and Blood Volume Pulse (BVP), were continuously acquired. This paper reported a novel feature selection method based on emotional state transition, and the results showed that the proposed method filter features more effectively.