Clinical feasibility of motor hotspot localization based on electroencephalography using convolutional neural networks in stroke.

ABSTRACT:

Background

Although transcranial magnetic stimulation (TMS) is the optimal tool for identifying individual motor hotspots-specific regions of the brain that are essential for controlling voluntary muscle movements-it involves a cumbersome procedure that requires patients to visit the hospital regularly and relies on expert judgment. To address this, we propose an advanced electroencephalography (EEG)-based motor hotspot identification algorithm using a deep-learning and assess its clinical feasibility and benefits by applying it to EEGs for stroke patients, considering the noticeable variations in EEG patterns between stroke patients and healthy controls.

Methods

Motor hotspot locations were estimated using a two-dimensional convolutional neural network (CNN) model. We utili

SUBMITTER: Choi GY 

PROVIDER: S-EPMC12465479 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature