Combining Robotic Vision with Non-Invasive Brain-Computer Interfaces Development and Future Directions

Abstract

The profound growth in brain-computer interface (BCI) technology has brought forth novel interdisciplinary applications, particularly in the realm of robotics. This review delves into the challenges of using non-invasive BCIs for precise robotic arm operations, with an emphasis on the transformative potential of integrating BCI with machine vision. Based on some problems in BCI applications, this paper emphasizes the use of machine vision combined with BCI signals to help non-invasive brain-computer interfaces improve the correctness and efficiency. Through detailed analysis, it is demonstrated how computer vision complements BCI, ameliorating issues like inherent noise and decoding inefficiencies associated with non-invasive BCIs. Moreover, the discussion touches upon the enhanced user experience offered by this integrated approach, and the potential it holds for addressing the compatibility challenges in BCIs. Although the combination of the two technologies can solve mutual problems, there are also certain limitations. For example, two different data may be more complex, so there are higher requirements for algorithms and processing methods. In addition, the development of a combination of two devices The system will have higher overhead, making it impossible for the average person to afford the cost of using it at the same time。As BCI technology continues its upward trajectory, this synthesis with robotic vision heralds a new era of harmonized human-machine interactions.