Recent Developments and Challenges in SSVEP-Driven Smart Home Control Systems

Steady-State Visual Evoked Potential (SSVEP)-based Brain-Computer Interfaces (BCIs) have gained significant attention as non-invasive, efficient means to enable paralyzed patients and individuals with severe motor impairments to control smart home environments. This review integrates research findings from 2022 to 2025, highlighting advances in stimulus paradigms, signal processing, classification algorithms, and system implementations involving embedded platforms and augmented reality. Key developments include generative adversarial networks for data augmentation, hybrid BCIs combining SSVEP with other modalities, adaptive ensemble classifiers, and velocity modulation for robotic control. Challenges such as visual fatigue, calibration requirements, user variability, and real-world performance constraints are addressed. The review emphasizes the growing feasibility and effectiveness of SSVEP-BCI systems in facilitating independent living through intuitive brain-driven smart home control.