Deep learning in fNIRS: a review
Condell Eastmond, Aseem Subedi, Suvranu De, Xavier Intes
Abstract
Significance: Optical neuroimaging has become a well-established clinical and research tool to monitor cortical activations in the human brain. It is notable that outcomes of functional nearinfrared spectroscopy (fNIRS) studies depend heavily on the data processing pipeline and classification model employed. Recently, deep learning (DL) methodologies have demonstrated fast and accurate performances in data processing and classification tasks across many biomedical fields.
Topics & Concepts
Functional near-infrared spectroscopyComputer scienceArtificial intelligencePreprocessorNeuroimagingDeep learningMachine learningPipeline (software)NeuroscienceCognitionPsychologyPrefrontal cortexProgramming languageEEG and Brain-Computer InterfacesOptical Imaging and Spectroscopy TechniquesFunctional Brain Connectivity Studies