Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task

Authors: Sharif Natheir, Sommer Christie, Recai Yilmaz, Alexander Winkler-Schwartz, Khalid Bajunaid, Abdulrahman J Sabbagh, Penny Werthner, Jawad Fares, Hamed Azarnoush, Rolando Del Maestro

Publication date: 2023

Journal: Computers in Biology and Medicine

Publisher: Pergamon

Description: Virtual reality surgical simulators have facilitated surgical education by providing a safe training environment. Electroencephalography (EEG) has been employed to assess neuroelectric activity during surgical performance. Machine learning (ML) has been applied to analyze EEG data split into frequency bands. Although EEG is widely used in fields requiring expert performance, it has yet been used to classify surgical expertise. Thus, the goals of this study were to (a) develop an ML model to accurately differentiate skilled and less-skilled performance using EEG data recorded during a simulated surgery, (b) explore the relative importance of each EEG bandwidth to expertise, and (c) analyze differences in EEG band powers between skilled and less-skilled individuals. We hypothesized that EEG recordings during a virtual reality surgery task would accurately predict the expertise level of the participant. Twenty-one …

Total citations: 3

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Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task

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Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task