Objective The purpose of this study is to investigate the cortical activation during passive and active training modes under different speeds of upper extremity rehabilitation robots. Methods Twelve healthy subjects completed the active and passive training modes at various speeds (0.12, 0.18, and 0.24 m/s) for the right upper limb. The functional near-infrared spectroscopy (fNIRS) was used to measure the neural activities of the sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and prefrontal cortex (PFC). Results Both the active and passive training modes can activate SMC, PMC, SMA, and PFC. The activation level of active training is higher than that of passive training. At the speed of 0.12 m/s, there is no significant difference in the intensity of the two modes. However, at the speed of 0.24 m/s, there are significant differences between the two modes in activation levels of each region of interest (ROI) (P < 0.05) (SMC: F = 8.90, P = 0.003; PMC: F = 8.26, P = 0.005; SMA: F = 5.53, P = 0.023; PFC: F = 9.160, P = 0.003). Conclusion This study mainly studied on the neural mechanisms of active and passive training modes at different speeds based on the end-effector upper-limb rehabilitation robot. Slow, active training better facilitated the cortical activation associated with cognition and motor control. See Video Abstract, http://links.lww.com/WNR/A621.

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BACKGROUND: There are few isometric training systems based on upper limb rehabilitation robots. Its efficacy and neural mechanism are not well understood. OBJECTIVE: This study aims to investigate the cortex activation of dynamic resistance and static (isometric) training based on upper limb rehabilitation robot combined with virtual reality (VR) interaction by using functional near-infrared spectroscopy (fNIRS). METHODS: Twenty subjects were included in this study. The experiment adopts the block paradigm design. Experiment in dynamic and static conditions consisted of three trials, each consisting of task (60 s)-rest (40 s). The neural activities of the sensorimotor cortex (SMC), premotor cortex (PMC) and prefrontal cortex (PFC) were measured. The cortex activation and functional connectivity (FC) were analyzed. RESULTS: Both the dynamic and static training can activate SMC, PMC, and PFC. In SMC and PMC, the activation of static training was stronger than dynamic training, there were significant differences between the two modes of each region of interest (ROI) (p <  0.05) (SMC: p = 0.022, ES = 0.72, PMC: p = 0.039, ES = 0.63). Besides, the FC between all ROIs of the static training was stronger than that of the dynamic training. CONCLUSION: The static training based on upper limb rehabilitation robot may better facilitate the cortical activation associated with motor control.

ObjectiveThis study aimed to evaluate the effects of multiple virtual reality (VR) interaction modalities based on force-haptic feedback combined with visual or auditory feedback in different ways on cerebral cortical activation by functional near-infrared spectroscopy (fNIRS). Methods: A modular multi-sensory VR interaction system based on a planar upper-limb rehabilitation robot was developed. Twenty healthy participants completed active elbow flexion and extension training in four VR interaction patterns, including haptic (H), haptic + auditory (HA), haptic + visual (HV), and haptic + visual + auditory (HVA). Cortical activation changes in the sensorimotor cortex (SMC), premotor cortex (PMC), and prefrontal cortex (PFC) were measured.ResultsFour interaction patterns all had significant activation effects on the motor and cognitive regions of the cerebral cortex (p &lt; 0.05). Among them, in the HVA interaction mode, the cortical activation of each ROI was the strongest, followed by HV, HA, and H. The connectivity between channels of SMC and bilateral PFC, as well as the connectivity between channels in PMC, was the strongest under HVA and HV conditions. Besides, the two-way ANOVA of visual and auditory feedback showed that it was difficult for auditory feedback to have a strong impact on activation without visual feedback. In addition, under the condition of visual feedback, the effect of fusion auditory feedback on the activation degree was significantly higher than that of no auditory feedback.ConclusionsThe interaction mode of visual, auditory, and haptic multi-sensory integration is conducive to stronger cortical activation and cognitive control. Besides, there is an interaction effect between visual and auditory feedback, thus improving the cortical activation level. This research enriches the research on activation and connectivity of cognitive and motor cortex in the process of modular multi-sensory interaction training of rehabilitation robots. These conclusions provide a theoretical basis for the optimal design of the interaction mode of the rehabilitation robot and the possible scheme of clinical VR rehabilitation.