Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150713
Title: A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson’s disease
Authors: Wan, Kai Rui
Maszczyk, Tomasz
See, Angela An Qi
Dauwels, Justin
King, Nicolas Kon Kam
Keywords: Science::Medicine
Issue Date: 2019
Source: Wan, K. R., Maszczyk, T., See, A. A. Q., Dauwels, J. & King, N. K. K. (2019). A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson’s disease. Clinical Neurophysiology, 130(1), 145-154. https://dx.doi.org/10.1016/j.clinph.2018.09.018
Project: NMRC/CNIG/1173/2017
Journal: Clinical Neurophysiology
Abstract: Objective: This study seeks to systematically review the selection of features and algorithms for machine learning and automation in deep brain stimulation surgery (DBS) for Parkinson’s disease. This will assist in consolidating current knowledge and accuracy levels to allow greater understanding and research to be performed in automating this process, which could lead to improved clinical outcomes. Methods: A systematic literature review search was conducted for all studies that utilized machine learning and DBS in Parkinson’s disease. Results: Ten studies were identified from 2006 utilizing machine learning in DBS surgery for Parkinson’s disease. Different combinations of both spike independent and spike dependent features have been utilized with different machine learning algorithms to attempt to delineate the subthalamic nucleus (STN) and its surrounding structures. Conclusion: The state-of-the-art algorithms achieve good accuracy and error rates with relatively short computing time, however, the currently achievable accuracy is not sufficiently robust enough for clinical practice. Moreover, further research is required for identifying subterritories of the STN. Significance: This is a comprehensive summary of current machine learning algorithms that discriminate the STN and its adjacent structures for DBS surgery in Parkinson’s disease.
URI: https://hdl.handle.net/10356/150713
ISSN: 1388-2457
DOI: 10.1016/j.clinph.2018.09.018
Rights: © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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