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Estimation of ANT-DBS Electrodes on Target Positioning Based on a New Percept (TM) PC LFP Signal Analysis

Title
Estimation of ANT-DBS Electrodes on Target Positioning Based on a New Percept (TM) PC LFP Signal Analysis
Type
Article in International Scientific Journal
Year
2022
Authors
Lopes, EM
(Author)
Other
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Rego, R
(Author)
Other
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Rito, M
(Author)
Other
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Chamadoira, C
(Author)
Other
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Dias, D
(Author)
Other
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Journal
Title: SensorsImported from Authenticus Search for Journal Publications
Vol. 22 No. 4
Final page: 6601
ISSN: 1424-3210
Publisher: MDPI
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Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
Publicação em Scopus Scopus - 0 Citations
Other information
Authenticus ID: P-00X-4RZ
Abstract (EN): Deep brain stimulation of the Anterior Nucleus of the Thalamus (ANT-DBS) is an effective therapy in epilepsy. Poorer surgical outcomes are related to deviations of the lead from the ANT-target. The target identification relies on the visualization of anatomical structures by medical imaging, which presents some disadvantages. This study aims to research whether ANT-LFPs recorded with the Percept (TM) PC neurostimulator can be an asset in the identification of the DBS-target. For this purpose, 17 features were extracted from LFPs recorded from a single patient, who stayed at an Epilepsy Monitoring Unit for a 5-day period. Features were then integrated into two machine learning (ML)-based methodologies, according to different LFP bipolar montages: Pass1 (nonadjacent channels) and Pass2 (adjacent channels). We obtained an accuracy of 76.6% for the Pass1-classifier and 83.33% for the Pass2-classifier in distinguishing locations completely inserted in the target and completely outside. Then, both classifiers were used to predict the target percentage of all combinations, and we found that contacts 3 (left hemisphere) and 2 and 3 (right hemisphere) presented higher signatures of the ANT-target, which agreed with the medical images. This result opens a new window of opportunity for the use of LFPs in the guidance of DBS target identification.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 13
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