Effect of Parallel Cognitive-Motor Training Tasks on Hemodynamic Responses in Robot-Assisted Rehabilitation.

Abstract

Objective: Previous studies suggest that the combination of robot-assisted training with other concurrent tasks may promote the functional recovery and improvement better than the single task. It is well-established that robot-assisted rehabilitation training is effective. This study aims to characterize the neural mechanisms and inter-regional connectivity changes associated with robot-assisted parallel interactive training tasks. Methods: Twenty-five healthy young adults (12 females and 13 males) participated in three number-related cognitive-motor parallel interactive training tasks categorized by difficulty: low difficulty (LD), medium difficulty (MD), and high difficulty (HD). Functional near-infrared spectroscopy was used to measure neural responses in the primary sensorimotor cortex (SM1), supplementary motor area (SMA), and prefrontal cortex (PFC). Activation maps and functional connectivity (FC) correlation matrix maps were applied to assess cortical response and connectivity among channels and regions of interest. Results: Significant differences were observed in both activation and connectivity results across the three training conditions. Stronger activation (p < 0.01) in oxy-hemoglobin was found in the MD conditions, with activation in the HD condition being stronger than in the LD condition. The FC in the PFC increased linearly with rising training difficulty. Trends in FC for SM1 and SMA were consistent with the activation results. Conclusions: In parallel training tasks of varying difficulty, MD stimulates more neural activity and promotes stronger network connections in the brain. This study enhances the understanding of the neurological processes involved in robot-assisted parallel interactive tasks and may inform more effective robot-assisted rehabilitation therapies. Impact Statement This study aims to characterize the neural mechanisms and inter-regional connectivity changes of robot-assisted parallel interactive training tasks when coping with changes in task difficulty. It presented an initial increase in activation and connectivity, but a decreasing trend when the excessive load was involved. Moderate difficulty training may stimulate more neural activity and network connections of the brain because it is challenging and acceptable. Our results suggest a relatively optimal condition for the implementation of robot-assisted rehabilitation in terms of training difficulty. It may provide a reference for more effective robot-assisted rehabilitation therapy.