fNIRS-based brain functional response to robot-assisted training for upper-limb in stroke patients with hemiplegia

Abstract

BackgroundRobot-assisted therapy (RAT) has received considerable attention in stroke motor rehabilitation. Characteristics of brain functional response associated with RAT would provide a theoretical basis for choosing the appropriate protocol for a patient. However, the cortical response induced by RAT remains to be fully elucidated due to the lack of dynamic brain functional assessment tools.ObjectiveTo guide the implementation of clinical therapy, this study focused on the brain functional responses induced by RAT in patients with different degrees of motor impairment.MethodsA total of 32 stroke patients were classified into a low score group (severe impairment, n = 16) and a high score group (moderate impairment, n = 16) according to the motor function of the upper limb and then underwent RAT training in assistive mode with simultaneous cerebral haemodynamic measurement by functional near-infrared spectroscopy (fNIRS). Functional connectivity (FC) and the hemisphere autonomy index (HAI) were calculated based on the wavelet phase coherence among fNIRS signals covering bilateral prefrontal, motor and occipital areas.ResultsSpecific cortical network response related to RAT was observed in patients with unilateral moderate-to-severe motor deficits in the subacute stage. Compared with patients with moderate dysfunction, patients with severe impairment showed a wide range of significant FC responses in the bilateral hemispheres induced by RAT with the assistive mode, especially task-related involvement of ipsilesional supplementary motor areas.ConclusionUnder assisted mode, RAT-related extensive cortical response in patients with severe dysfunction might contribute to brain functional organization during motor performance, which is considered the basic neural substrate of motor-related processes. In contrast, the limited cortical response related to RAT in patients with moderate dysfunction may indicate that the training intensity needs to be adjusted in time according to the brain functional state. fNIRS-based assessment of brain functional response assumes great importance for the customization of an appropriate protocol training in the clinical practice.

Effects of training with a rehabilitation device (Rebless®) on upper limb function in patients with chronic stroke: A randomized controlled trial

“…Several studies have utilized fNIRS to compare cortical activity before and after upper limb training with robotic devices in patients who have experienced a stroke. [11][12][13][14][15] One study conducted robot-assisted therapy in stroke patients with hemiplegia, using fNIRS to compare cortical activity between groups with severe and moderate impairments. [13] However, to the best of our knowledge, few studies are using fNIRS to compare cortical activity after training with a robotic device and conventional device for upper limb rehabilitation in patients with stroke.…”

“…[10] Several studies have utilized fNIRS to compare cortical activity before and after upper limb training with robotic devices in patients with stroke. [11][12][13][14][15] However, there is a particular paucity of research comparing the effects of robotic versus conventional devices on cortical activity during upper limb rehabilitation in patients with stroke.…”

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging During Rehabilitation Following Stroke: A Review

“…This shows that stroke patients exhibit right hemispheric involvement in compensation when compared to healthy individuals. A study investigating brain function in patients with different levels of motor dysfunction [ 29 ] discovered that patients with severe dysfunction displayed considerable hemispheric functional connectivity in the upper-limb motor assistance mode, bilaterally involving prefrontal, motor, and occipital areas, in contrast to patients with moderate dysfunction. Furthermore, the study revealed a significant increase in the involvement of ipsilateral assistive motor areas in the functional brain network.…”

Functional connectivity and graph theory of impaired central visual pathways in acute ischemic stroke based on fMRI

“…In stroke patients, most resting-state functional connectivity studies are based on the a priori selection of seed regions [15] , which cannot provide information on the brain-wide change characteristics of FC, so there is a need for brain-wide static functional connectivity studies to investigate the underlying neurobiological mechanisms. The brain is a highly synergistic and integrated network, and continuous and uninterrupted intrinsic brain activity is an important feature of healthy brain function [16] [17] . It has been found that functional connectivity re ects neuroanatomical features that allow assessment of the intrinsic transmission of neural information within the network [18] [19] , and that resting-state brain activity spatially organises neural activity in a speci c coherent pattern.SFC, a model and data-driven algorithm based on resting-state fMRI, is characterised by the absence of hypothetical analyses of a priori knowledge, and the whole-brain-wide ROIs of Intergroup variability analysis can clarify the interaction mechanism between ROIs.…”