Joseline Veit
Papers
1
Total Citations
2
H-Index
1
About
Joseline Veit is pioneering accessible assistive robotics through non-invasive brain-computer interfaces (BCIs). Her research centers on developing screen-free, intuitive control systems that allow users to communicate high-level goals—such as selecting objects for a robot to fetch—using only neural signals. Veit’s most cited work, “A Robust Screen-Free Brain-Computer Interface for Robotic Object Selection” (2020), introduces a paradigm where the robot visually highlights candidate objects, enabling users to make selections without traditional screens or manual input. This approach significantly enhances autonomy for individuals with severe motor impairments. While her citation count is still growing, Veit’s contributions are notable for their focus on real-world usability and robustness, addressing critical challenges in BCI reliability and user experience. Her work sits at the intersection of neuroscience, robotics, and human-computer interaction, offering a glimpse into a future where assistive technologies respond directly to thought. Veit’s research is particularly impactful for students and engineers seeking to bridge the gap between laboratory BCI demonstrations and practical, everyday assistive devices.
Research Focus
Key Achievements
Top Papers
- 1