Explainable artificial intelligence model to predict brain states from fNIRS signals

Explainable artificial intelligence model to predict brain states from fNIRS signals

Objective: Most Deep Learning (DL) methods for the classification of functional Near-Infrared Spectroscopy (fNIRS) signals do so without explaining which features contribute to the classification of a task or imagery. An explainable artificial intelligence (xAI) system that can decompose the Deep Le...

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Bibliographic Details
Main Authors: Caleb Jones Shibu, Sujesh Sreedharan, KM Arun, Chandrasekharan Kesavadas, Ranganatha Sitaram
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-01-01
Series:Frontiers in Human Neuroscience
Subjects:
brain state classification
functional near-infrared spectroscopy
brain-computer interface
deep learning
convolutional neural networks
long short-term memory
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2022.1029784/full

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https://www.frontiersin.org/articles/10.3389/fnhum.2022.1029784/full

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