## 4 Discussion  
In the present study, an fNIRS device was used to monitor the activation of brain regions in elderly people with MCI during the completion of a VR task. fNIRS is a reliable functional brain-imaging technique, and its stability improves the monitoring of changes in neural activity during the experiment [32]. The analysis of experimental data in this paper was based on wavelet amplitudes, which can reflect frequency information regarding changes in neural activity in the cerebral cortex at any moment [33], and is suitable for analysis and discussion in the context of measurement tasks [34]. This study estimated that the cognition level of older adults affects their ability to respond to product interactions. The results showed that the cognitive level of the group that completed the task was significantly higher than that of the group who left the task incomplete. The WA of brain areas in the completion group was also significantly higher than that of the incompletion group. We believe that this change in wavelet amplitude is related to the level of awareness. Brain areas are significantly activated when an individual participates in cognizant visual movement or develops an extraordinary idea [35]. This is consistent with previous studies that used EEG devices to monitor users' cognitive workload during interactions with VR products [36]. Neither group had been exposed to such products previously, and both completed the experiment during the same timeframe. The results for both groups clearly showed a high level of cognition, mastery, and comprehension in the group that completed the task. [PERSON], [PERSON] et al. [37; 38] alluded to a correlation between the interactive body and cognitive level, and  
Figure 8: Correlation analysis of WA and behavioral indicators in PFL. Figure 7: Correlation analysis of median upper limb, discrete stable ratio and cognitive level. stated that the user's cognitive level is reflected in their interaction with the product. Thus, users with a higher cognitive level have an interactive responsiveness that is strong enough to allow for them to complete the task within the required time, while the group that left the task incomplete, as shown in all aspects of the results, had relatively weak cognitive abilities and showed a low level of product understanding during the task. VR-based products can stimulate the brains of MCI older adults [39; 40], especially older adult groups with relatively low cognitive levels [14]. The results showed that two regions, ROL and LOL, were significantly activated in the incomplete group, and that OL is crucial for processing visual information and plays an important role in the coordination of language, perception, and abstraction [41]. The products in the experiment had high brightness and pure, clear colors, and were in the main field of vision; thus, they provided a more intense visual stimulus to the occipital lobe (OL) area. The behavioral data of the uncompleted and completed bunches showed that those who completed the task had a fundamentally higher general upper-appendage speed compared to the group who did not complete the task, in addition to an average upper-appendage speed increase. The correlation between RPFC, LPFC, and upper-limb movements in the task suggests that VR-based products act together through multimodal senses, and subjects form their behavioral responses through information integration, which requires coordination between attention and sensorimotor functions. This may ex-plain the association between cognitive areas and movements. The cognition level also affects sensorimotor function, and a decrease in cognitive ability leads to a decrease in motor ability [42]. Long-term video-game training enhances functional integration between attention and sensory-motor networks [43], and VR-based products with audiovisual multidimensional sensory and rich picture effects are can promote complex brain system constructs, which is consistent with the results obtained from previous studies [44].