A direct classification approach to recognize stress levels in virtual reality therapy for patients with multiple sclerosis. (22nd September 2021)

• Record Type: Journal Article
• Authors: Rezaee, Khosro; Zolfaghari, Shina
• Other Names: Lv Zhihan guestEditor.; Lloret Jaime guestEditor.; Song Houbing guestEditor.
• Is Part Of: Computational intelligence. Volume 38:Number 1(2022)
• Page Start: 249
• Page End: 268
• Publication Date: 2021-09-22
• Subjects: fractal descriptor -- multiple sclerosis -- physiological signals -- support vector machine -- virtual reality; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12480
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: Multiple sclerosis (MS) is a chronic, debilitating, and often progressive inflammatory disease of the nervous system. The disease is highly stressful, which accelerates the risk of depression in people diagnosed with it and possibly exacerbates MS activity. One approach to reducing stress levels in such patients is to utilize virtual reality (VR). Using VR technology and recording physiological signals before and after displaying different environments to the individual, this article proposed a novel therapy procedure for improving stress levels. In the first phase, by distinguishing the stress level obtained from each environment watched by the patient, their corresponding labels are determined by two psychiatrists. Accordingly, the automated model is designed based on the analysis of VR scenes and can accurately classify MS patients' stress levels after watching the 3D environment. The proposed model consists of a fractal descriptor and SVM‐RBF classifier to recognize VR scenes that can significantly reduce the stress level in MS patients. The accuracy of estimating MS patients' stress levels after watching different simulated VR environments is higher than 97%. By employing this method to classify VR scenes better and rehabilitate MS patients, it will be possible to significantly reduce their stress levels.