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Exploring the Multimodal Integration of VR and MRI Biomarkers for Enhanced Early Detection of Mild Cognitive Impairment

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Kyoungwon SeoAuthors Info & Claims

CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

Article No.: 155, Pages 1 - 8

https://doi.org/10.1145/3613905.3651108

Published: 11 May 2024 Publication History

Abstract

Early detection of mild cognitive impairment (MCI) is crucial to impede dementia progression. Virtual reality (VR) biomarkers are adept at detecting impairments in instrumental activities of daily living (IADL), whereas magnetic resonance imaging (MRI) biomarkers excel in measuring observable structural changes in the brain. However, the efficacy of integrating VR and MRI biomarkers to improve early MCI detection remains unclear. This study aims to evaluate and compare the effectiveness of VR and MRI biomarkers and investigates the potential of their combined use for more accurate early MCI detection. Through support vector machine analysis, distinct characteristics were observed. For identifying MCI, VR biomarkers demonstrated high specificity (90.0%), whereas MRI showed high sensitivity (90.9%). The combination of both biomarkers yielded superior results in accuracy (94.4%), sensitivity (100.0%), and specificity (90.9%). Drawing from these results, we suggest a sequential diagnostic approach, employing VR for initial screening and MRI for subsequent confirmation of MCI.

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Cited By

Kallel MPark BSeo KKim S(2024)Multimodal Machine Learning Model For MCI Detection Using EEG, MRI and VR Data2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)10.1109/ITC-CSCC62988.2024.10628204(1-6)Online publication date: 2-Jul-2024
https://doi.org/10.1109/ITC-CSCC62988.2024.10628204
Park BPark JChoi HRyu HSeo K(2024)Advancing Mild Cognitive Impairment Detection: Integrating VR, MRI, and Neuropsychological Insights for Comprehensive Diagnosis2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)10.1109/ITC-CSCC62988.2024.10628151(1-6)Online publication date: 2-Jul-2024
https://doi.org/10.1109/ITC-CSCC62988.2024.10628151

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Exploring the Multimodal Integration of VR and MRI Biomarkers for Enhanced Early Detection of Mild Cognitive Impairment

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CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

May 2024

4761 pages

ISBN:9798400703317

DOI:10.1145/3613905

Editors:
Florian Floyd Mueller
Monash University
,
Penny Kyburz
The Australian National University
,
Julie R. Williamson
University of Glasgow
,
Corina Sas
Lancaster University

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Published: 11 May 2024

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This work was supported by Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (RS-2023-00262158).

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Cited By

Kallel MPark BSeo KKim S(2024)Multimodal Machine Learning Model For MCI Detection Using EEG, MRI and VR Data2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)10.1109/ITC-CSCC62988.2024.10628204(1-6)Online publication date: 2-Jul-2024
https://doi.org/10.1109/ITC-CSCC62988.2024.10628204
Park BPark JChoi HRyu HSeo K(2024)Advancing Mild Cognitive Impairment Detection: Integrating VR, MRI, and Neuropsychological Insights for Comprehensive Diagnosis2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)10.1109/ITC-CSCC62988.2024.10628151(1-6)Online publication date: 2-Jul-2024
https://doi.org/10.1109/ITC-CSCC62988.2024.10628151

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