## 5 Conclusions  
Integrating BCI with VR improves the performance of brain-computer interfaces in IoT control by providing immersive, adaptive training environments that increase signal accuracy and user control. VR offers real-time feedback and simulations that help users refine their interactions with smart home systems, making the interface more intuitive and responsive. This combination ultimately leads to greater independence, efficiency, and ease of use, especially for users with mobility issues, in managing IoT-connected devices.  
The integration of brain-computer interfaces and virtual reality has shown immense potential for transforming a diverse array of applications, from neurorehabilitation and human-computer interaction to cognitive assessment and personalized therapeutic interventions for various neurological and cognitive disorders. The reviewed literature underscores the significant advancements and the multifaceted challenges in this rapidly evolving field.  
Particularly noteworthy is the emphasis on the importance of adaptive signal processing techniques, which enable BCI-VR systems to dynamically optimize their performance by adjusting parameters like time-window length to better accommodate the user's brain activity in real-time. This adaptability is crucial for enhancing the overall control and immersion experienced by individuals within virtual environments.  
Furthermore, the reviewed studies highlight the value of multimodal integration, where BCI technology is combined with complementary biosensors like eye-tracking and motion capture. This synergistic approach allows for more comprehensive and accurate assessments of cognitive and motor functions, ultimately leading to more personalized and effective therapeutic interventions.  
Lastly, the incorporation of advanced artificial intelligence techniques, such as machine learning and natural language processing, holds immense promise for revolutionizing the way clinicians approach the diagnosis and management of conditions like mild cognitive impairment. The integration of AI-powered systems like ChatGPT can enable deeper analysis of patient data, more precise identification of cognitive deficits, and the development of tailored treatment strategies.  
Overall, the seamless integration of BCIs and VR, coupled with the advancements in adaptive signal processing, multimodal integration, and AI-driven technologies, presents a transformative opportunity to redefine the landscape of neurorehabilitation, human-computer interaction, and personalized cognitive interventions. As this field continues to evolve, the potential for enhancing quality of life and improving clinical outcomes for individuals with neurological and cognitive disorders is truly remarkable.  
Conceptualization, A.P., I.R. and D.M.; methodology, A.P., I.R. and D.M.; software, A.P., I.R. and D.M.; validation, A.P., I.R. and D.M.; formal analysis, A.P., I.R. and D.M.; investigation, A.P., I.R. and D.M.; resources, A.P., I.R. and D.M.; data curation, A.P., I.R. and D.M.; writing--original draft preparation, A.P., I.R. and D.M.; writing--review and editing, A.P., I.R. and D.M.; supervision, I.R.; project administration, I.R.; funding acquisition, I.R. All authors have read and agreed to the published version of the manuscript.  
The work presented in this paper has been financed under a grant to maintain the re- search potential of Kazimierz Wielki University.  
Not applicable.  
The authors declare no conflicts of interest.