Autism Spectrum Disorder (ASD) impacts social interaction, communication, and cognitive functioning. In recent years, virtual reality (VR) technology, with its advantages such as strong immersive capabilities, has been increasingly applied to ASD ergotherapy. However, existing systems often overlook human factors considerations, including users' perceptual preferences and attentional load during system interactions. This study proposes a Personalized Multisensory Adaptive Roaming System (P-MARS), which integrates large-scale models to analyze users' sensory preferences and generates personalized VR scenarios combined with visual, auditory, and olfactory stimuli, aiming to enhance ergotherapy outcomes for children with ASD. A longitudinal study employing functional near-infrared spectroscopy (fNIRS) was conducted to assess participants' neural states. The results demonstrate a significant reduction in central neural activation levels among children during the later stages of training. These findings suggest that periodic VR-based training can substantially alleviate cognitive load and anxiety in children with ASD, thereby accelerating ergotherapy progress. The study further validates the critical importance and efficacy of incorporating human factors into ergotherapy system design.