This study examines the present status, challenges, and future trajectories of employing electroencephalography (EEG) technology to assess the efficacy of virtual reality exposure therapy (VRET) in the treatment of acrophobia through a systematic review and comparative analysis of 10 pertinent studies. The results indicate that EEG’s superior temporal resolution can effectively detect increased theta waves and alterations in prefrontal lobe activity when patients encounter virtual height situations. In addition, microstate analysis and functional brain network (FBN) can effectively distinguish between different severity levels of acrophobia. Immersive design elements of virtual scenes (such as dynamic height adjustments and environmental vibrations) significantly enhance the validity of fear stimuli, but existing studies have significant deficiencies in sample diversity (gender and age), standardization of EEG data (number of channels and preprocessing workflows), and consistency of scene parameters. Experimental results indicate that combining multimodal machine learning with deep learning feature extraction can increase classification accuracy to 85.7%. Future research should focus on standardizing experimental procedures, optimizing cross‐cultural scenarios, and integrating multimodal data to promote the scientific and precise application of VRET in clinical settings.
Pan et al. (Thu,) studied this question.