VRNPT: A Neuropsychological Test Tool for Diagnosing Mild Cognitive Impairment Using Virtual Reality and EEG Signals

AbstractMild cognitive impairment is associated with many neurodegenerative diseases. It is essential to detect mild cognitive impairment on time to reduce the prevalence of such disorders. Nevertheless, present clinically employed test scales and biomarkers are time-consuming, user-unfriendly, and expensive. Hence, we developed a neuropsychological test system based on virtual reality in this study, the Virtual Reality Neuropsychological Mild Cognitive Impairment Test (VRNPT). The diagnosis and classification of MCI were achieved by effectively combining digital cognitive parameters and EEG signal features obtained during the VRNPT cognitive task. The VRNPT contains three head-mounted display-based cognitive tasks that assess participants' attention, memory, spatial perception, working memory, and visuospatial executive ability across multiple cognitive domains of functioning. We investigated how to design and optimize these tasks. We conducted a field study by recruiting 80 participants (40 MCI patients and 40 normal older adults). The results showed that the classification accuracy of combining digitized cognitive parameters and EEG signals during VRNPT was 91.3%, higher than using only digitized parameters from VRNPT and applying EEG signals alone, demonstrating the validity and feasibility of this method for diagnosing MCI. The user satisfaction survey showed that the subjects were satisfied with VRNPT.Keywords: Mild cognitive impairmentelectroencephalogramimmersive virtual realitywearable devicesscreening tool Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Natural Science Foundation of China under Grant number U21A20469; The Central Government Guides Local Science and Technology Development Fund Project under Grant number [YDZJSX2022C004].Notes on contributorsChen XueChen Xue received his BS from Taiyuan University of Technology, China, in 2021. He is pursuing his Master's degree in the Department of Computer Science at the Taiyuan University of Technology. His research interests include virtual reality and wearable computing.Aoyu LiAoyu Li received his Master's degree from Xi'an University of Technology, China 2017. He is pursuing his PhD in Computer Science at Taiyuan University of Technology, China. His research interests include pervasive computing and virtual reality.Ruixuan WuRuixuan Wu received her BS degree from Taiyuan University of Technology, China, in 2021. She is pursuing her Master's degree in the Department of Computer Science at the Taiyuan University of Technology. Her research interests include virtual reality and human-computer interaction.Jiali ChaiJiali Chai received her BS degree from Dalian Jiaotong University, China, in 2019. She has received a master's degree from the Department of Information Studies at the Taiyuan University of Technology. Her research interests include interface design and evaluation and virtual reality.Yan QiangYan Qiang is currently a professor at the School of Computer Science and Technology, Taiyuan University of Technology, and a standing member of the Human-Computer Interaction Specialized Committee of the Chinese Computer Society. His research interests include human-computer interaction and virtual reality.Juanjuan ZhaoJuanjuan Zhao is currently a professor at the School of Computer Science and Technology, Taiyuan University of Technology, and a member of the Human-Computer Interaction Specialized Committee of the Chinese Computer Society. Her research interests include image processing and virtual reality.Qianqian YangQianqian Yang is a lecturer and senior engineer at Jinzhong College of Information, China. Her research interests include virtual reality and database application technology.