This paper is in the following e-collection/theme issue:

Extended Reality, Virtual Reality and Virtual Worlds (673) Computer-Aided Diagnosis (188) Machine Learning (1759) New Methods (1034) Wearable Devices and Sensors (1009) Decision Support for Health Professionals (1353) Artificial Intelligence (1766) Development and Evaluation of Research Methods, Instruments and Tools (644) Dementia and Cognitive Decline (597) Evaluation of XR and Spatial Computing (64)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48093, first published .
Digital Marker for Early Screening of Mild Cognitive Impairment Through Hand and Eye Movement Analysis in Virtual Reality Using Machine Learning: First Validation Study

Digital Marker for Early Screening of Mild Cognitive Impairment Through Hand and Eye Movement Analysis in Virtual Reality Using Machine Learning: First Validation Study

Digital Marker for Early Screening of Mild Cognitive Impairment Through Hand and Eye Movement Analysis in Virtual Reality Using Machine Learning: First Validation Study

Authors of this article:

Se Young Kim1 Author Orcid Image ;   Jinseok Park2 Author Orcid Image ;   Hojin Choi2 Author Orcid Image ;   Martin Loeser3 Author Orcid Image ;   Hokyoung Ryu4 Author Orcid Image ;   Kyoungwon Seo1 Author Orcid Image
Article Authors Cited by (19) Tweetations (3) Metrics

Journals

  1. Choi D, Park J, Loeser M, Seo K. Improving counseling effectiveness with virtual counselors through nonverbal compassion involving eye contact, facial mimicry, and head-nodding. Scientific Reports 2024;14(1) View
  2. Veneziani I, Marra A, Formica C, Grimaldi A, Marino S, Quartarone A, Maresca G. Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review. Journal of Personalized Medicine 2024;14(1):113 View
  3. Park B, Kim Y, Park J, Choi H, Kim S, Ryu H, Seo K. Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study. Journal of Medical Internet Research 2024;26:e54538 View
  4. Kim D, Kim Y, Park J, Choi H, Ryu H, Loeser M, Seo K. Exploring the Relationship between Behavioral and Neurological Impairments Due to Mild Cognitive Impairment: Correlation Study between Virtual Kiosk Test and EEG-SSVEP. Sensors 2024;24(11):3543 View
  5. Wang P, Ali N, Sarker M. A Bibliometric Analysis Exploring the Acceptance of Virtual Reality among Older Adults: A Review. Computers 2024;13(10):262 View
  6. Wang Y, Yang P, Yu J, Zhang S, Gong L, Liu C, Zhou W, Peng B. An Ensemble Learning Algorithm for Cognitive Evaluation by an Immersive Virtual Reality Supermarket. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2024;32:3761 View
  7. Farabi Maleki S, Yousefi M, Sobhi N, Jafarizadeh A, Alizadehsani R, Gorriz-Saez J. Artificial Intelligence in Eye Movements Analysis for Alzheimer’s Disease Early Diagnosis. Current Alzheimer Research 2024;21(3):155 View
  8. Kim D, Park J, Choi H, Ryu H, Loeser M, Seo K. Early Detection of Patients With Mild Cognitive Impairment Through EEG-SSVEP-Based Machine Learning Model. IEEE Access 2024;12:172101 View
  9. Bhargava Y, Kumar Kattupalli K, Baths V. CogTrack: A Proof of Concept for Cognition Tracker. IEEE Access 2024;12:194609 View
  10. Avilés-Castillo F, Buele J, Palacios-Navarro G. Virtual Reality and User Experience: Current Trends and Future Challenges. IEEE Access 2025;13:55939 View
  11. Shah H, Khalil S, Andberg S, Koivisto A, Bednarik R. Eye tracking based detection of mild cognitive impairment: A review. Information Fusion 2025;122:103202 View
  12. Sugianto M, Zhou Y, Qiu J. Eye tracking-based dual task in rehabilitation of motor and cognitive function in post-stroke patients: a literature review. Bulletin of Faculty of Physical Therapy 2025;30(1) View

Conference Proceedings

  1. Kim S, Park B, Kim D, Choi H, Park J, Ryu H, Seo K. 2024 International Conference on Electronics, Information, and Communication (ICEIC). Early Screening of Mild Cognitive Impairment using Multimodal VR-EP-EEG-MRI (VEEM) Biomarkers via Machine Learning View
  2. Kim Y, Park J, Choi H, Loeser M, Ryu H, Seo K. Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. Decoding Behavior: Utilizing Virtual Reality Digital Marker and Machine Learning for Early Detection of Mild Cognitive Impairment View
  3. Park B, Kim Y, Park J, Choi H, Kim S, Ryu H, Seo K. Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. Exploring the Multimodal Integration of VR and MRI Biomarkers for Enhanced Early Detection of Mild Cognitive Impairment View
  4. Park B, Park J, Choi H, Ryu H, Seo K. 2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC). Advancing Mild Cognitive Impairment Detection: Integrating VR, MRI, and Neuropsychological Insights for Comprehensive Diagnosis View
  5. Kallel M, Park B, Seo K, Kim S. 2024 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC). Multimodal Machine Learning Model For MCI Detection Using EEG, MRI and VR Data View
  6. Kim Y. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. Beyond Missing Data: A Multimodal Approach Using VR-EEG-MRI (VEEM) Biomarkers for Detecting MCI View
  7. Cha S, Park J, Choi H, Ryu H, Seo K. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. CLONE: Synthetic Guideline-based Clinical Reasoning with Large Language Models for Early Diagnosis of Mild Cognitive Impairment View