Application of Virtual Reality and Electrodermal Activity for the Detection of Cognitive Impairments
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Liverpool John Moores; Wageningen University; University of ChesterPublication Date
2022-03-01
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Mild Cognitive Impairment (MCI) is a definition of the diagnosis of early memory loss and disorientation. This study aims to identify people’s symptoms through technology. However, machine learning (ML) can classify Cognitive Normal (CN) and Mild Cognitive Impairment (MCI) and Early Mild Cognitive Impairment (EMCI) using standard assessments from the Alzheimer’s Disease Neuroimaging Initiative (ADNI); Montreal Cognitive (MoCA), Mini-Mental State Examination (MMSE), Functional Activities Questionnaire (FAQ). Consequently, a Multilayer Perceptron (MLP) model was assembled into tables; MCI vs CN, MCI vs EMCI, and CN vs MCI. Additionally, an MLP model was developed for CN vs MCI vs EMCI. As a result, of advanced model performance, a cascade 3-path categorisation approach was created. Similarly, the exploitation of meta-analysis indicated a combination of MLP models (MCI vs CN, MCI vs EMCI, and CN vs MCI) with an overall accuracy within an acceptable limit. In addition, better results were found when assessments were combined rather than individually. Furthermore, applying class weights and probability thresholds could improve the MLP framework by performance achieving a balanced specificity and sensitivity ratio. Altering class weights and probability thresholds when training the MLP neuro network model, the sensitivity and Accuracy could be progressed further. In conclusion, ML, VR and electrodermal activity are constrained. Introducing the possibility of activity-based applications to enhance innovative solutions for cognitive impairment diagnosis and treatment.Citation
Patient, R., Fawaz, G., Hoshang, K., Hurst, W. & John, N.W. (2021). Application of virtual reality and electrodermal activity for the detection of cognitive impairments. In 2021 14th International Conference on Developments in eSystems Engineering (pp. 156-161). Institute of Electrical and Electronics Engineers (IEEE).Publisher
IEEEAdditional Links
https://ieeexplore.ieee.org/xpl/conhome/1003085/all-proceedingsType
Conference ProceedingDescription
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISBN
9781665408899ae974a485f413a2113503eed53cd6c53
10.1109/DeSE54285.2021.9719442
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