Detecting Post-Stroke Aphasia Via Brain Responses to Speech in a Deep Learning Framework

no code implementations • 17 Jan 2024 • Pieter De Clercq, Corentin Puffay, Jill Kries, Hugo Van hamme, Maaike Vandermosten, Tom Francart, Jonas Vanthornhout

We modeled electroencephalography (EEG) responses to acoustic, segmentation, and linguistic speech representations of a story using convolutional neural networks trained on a large sample of healthy participants, serving as a model for intact neural tracking of speech.

EEG

Detecting post-stroke aphasia using EEG-based neural envelope tracking of natural speech

no code implementations • 14 Mar 2023 • Pieter De Clercq, Jill Kries, Ramtin Mehraram, Jonas Vanthornhout, Tom Francart, Maaike Vandermosten

In this study, we aimed to test the potential of the neural envelope tracking technique for detecting language impairments in individuals with aphasia (IWA).

EEG