Home-based portable fNIRS-derived cortical laterality correlates with impairment and function in chronic stroke

Abstract

IntroductionImproved understanding of the relationship between post-stroke rehabilitation interventions and functional motor outcomes could result in improvements in the efficacy of post-stroke physical rehabilitation. The laterality of motor cortex activity (M1-LAT) during paretic upper-extremity movement has been documented as a useful biomarker of post-stroke motor recovery. However, the expensive, labor intensive, and laboratory-based equipment required to take measurements of M1-LAT limit its potential clinical utility in improving post-stroke physical rehabilitation. The present study tested the ability of a mobile functional near-infrared spectroscopy (fNIRS) system (designed to enable independent measurement by stroke survivors) to measure cerebral hemodynamics at the motor cortex in the homes of chronic stroke survivors.MethodsEleven chronic stroke survivors, ranging widely in their level of upper-extremity motor deficit, used their stroke-affected upper-extremity to perform a simple unilateral movement protocol in their homes while a wireless prototype fNIRS headband took measurements at the motor cortex. Measures of participants' upper-extremity impairment and function were taken.ResultsParticipants demonstrated either a typically lateralized response, with an increase in contralateral relative oxyhemoglobin (ΔHbO), or response showing a bilateral pattern of increase in ΔHbO during the motor task. During the simple unilateral task, M1-LAT correlated significantly with measures of both upper-extremity impairment and function, indicating that participants with more severe motor deficits had more a more atypical (i.e., bilateral) pattern of lateralization.DiscussionThese results indicate it is feasible to gain M1-LAT measures from stroke survivors in their homes using fNIRS. These findings represent a preliminary step toward the goals of using ergonomic functional neuroimaging to improve post-stroke rehabilitative care, via the capture of neural biomarkers of post-stroke motor recovery, and/or via use as part of an accessible rehabilitation brain-computer-interface.

A Multiple Session Dataset of NIRS Recordings From Stroke Patients Controlling Brain–Computer Interface

“…In addition, brain activity classification can rely on several simultaneously measured quantities, including oxy--, deoxy--, and total hemoglobin concentrations. Only a few articles have been published on the use of NIRS--BCI after stroke [15][16][17].…”

Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback

“…Studies have been performed where VR has simulated an MRI experience ( [45]), VR has been used to prepare children for MRI ( [46]), and studies have used VR during hemoencephalographic ( [10]) and MRI sessions ( [47]). Recent studies have explored the use of fMRI VR-like stimuli to prepare PTSD patients for VR training ( [48]), machine learning of biofeedback to optimize VR exposure therapy ( [49]), the combination of biofeedback, VR, and mobile technology to enable home training through sham-feedback ( [50]), and NIRS neurofeedback for at-home use by patients ( [51]). To the best of the authors' knowledge, this is the first protocol aiming to explore how targeted use of contextual memory/VR immersion, and home training with sham-feedback may enhance subsequent real-time fMRI neurofeedback sessions.…”