Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/54794
Title: Evaluating Effects of Resting-State Electroencephalography Data Pre-Processing on a Machine Learning Task for Parkinson's Disease
Contributor(s): Vlieger, Robin  (author); Daskalaki, Elena (author); Apthorp, Deborah  (author)orcid ; Lueck, Christian J (author); Suominen, Hanna (author)
Publication Date: 2023-03-06
Open Access: Yes
DOI: 10.1101/2023.03.06.23286826Open Access Link
Handle Link: https://hdl.handle.net/1959.11/54794
Abstract: 

Resting-state electroencephalography (RSEEG) is a method under consideration as a potential biomarker that could support early and accurate diagnosis of Parkinson's disease (PD). RSEEG data is often contaminated by signals arising from other electrophysiological sources and the environment, necessitating pre-processing of the data prior to applying machine learning methods for classification. Importantly, using differing degrees of pre-processing will lead to different classification results. This study aimed to examine this by evaluating the difference in experimental results when using re-referenced data, data that had undergone filtering and artefact rejection, and data without muscle artefact. The results demonstrated that, using a Random Forest Classifier for feature selection and a Support Vector Machine for disease classification, different levels of pre-processing led to markedly different classification results. In particular, the presence of muscle artefact was associated with inflated classification accuracy, emphasising the importance of its removal as part of pre-processing.

Publication Type: Working Paper
Publisher: medRxiv
Place of Publication: United States of America
Fields of Research (FoR) 2020: 320904 Computational neuroscience (incl. mathematical neuroscience and theoretical neuroscience)
520105 Psychological methodology, design and analysis
Socio-Economic Objective (SEO) 2020: 280112 Expanding knowledge in the health sciences
HERDC Category Description: W Working Paper
Appears in Collections:School of Psychology
Working Paper

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