The use of functional near-infrared spectroscopy (fNIRS) for monitoring brain function, predicting outcomes, and evaluating rehabilitative interventional responses in poststroke patients with upper limb hemiplegia : a systematic review

Abstract

Functional near-infrared spectroscopy (fNIRS) has been increasingly applied in poststroke research. The accumulated evidence in this area warrants a comprehensive review systematically investigating the utility of fNIRS in poststroke rehabilitation, specifically focusing on upper limb motor recovery. The target of this systematic review was the use of fNIRS for monitoring brain function, predicting outcomes, and evaluating rehabilitative interventional responses in poststroke patients with upper limb hemiplegia. A literature search was carried out using PubMed, Web of Science, EMBASE, Medline, and IEEE Explore, to identify studies that applied fNIRS in stroke survivors. A total of 52 studies were included, with 23 cross-sectional studies, 8 longitudinal studies and 21 interventional studies. The majority of the included fNIRS studies displayed a bilateral activation pattern in patients after stroke during paretic upper limb movement. The change in hemispheric laterality, measured by oxygenated hemoglobin concentration changes (Δ[HbO]) levels in different corticomotor regions, has been found to be correlated with motor recovery following a stroke. Various rehabilitation interventions, such as exercise-based, stimulation-based, and neurofeedback techniques, improved recovery outcomes by increasing Δ[HbO] levels in the ipsilesional sensorimotor and secondary motor areas. These interventions also recruited different brain regions connected to the ipsilesional sensorimotor area, thereby strengthening their connectivity. In conclusion, outcomes derived from fNIRS demonstrate promise in monitoring brain function, predicting outcomes, and evaluating responses to interventions in patients after stroke. Future fNIRS research can be enhanced by adhering to best practice checklists, utilizing the latest experimental setup and analysis protocols, and recruiting large sample sizes.