Emilie Doat
Papers
2
Total Citations
14
H-Index
2
About
Emilie Doat is a researcher at the forefront of understanding human motor control and visual attention in virtual reality. Her primary research areas include 3D arm kinematics, gaze behavior, and the integration of multimodal sensory data during natural reaching movements. Doat’s major contribution is the creation of the **3D-ARM-Gaze dataset**, a publicly available resource that captures synchronized arm movements and eye-gaze information as participants reach for and manipulate objects across a wide, precisely controlled workspace. This dataset is invaluable for advancing human-computer interaction, rehabilitation robotics, and VR-based training systems. With combined citations of 14, the work has already gained traction in the research community for its rigorous methodology and practical relevance. Doat’s achievement lies in bridging a critical gap: providing naturalistic, high-fidelity data that enables researchers to model how vision guides action in immersive environments. Her efforts are paving the way for more intuitive VR interfaces and assistive technologies, making her a key contributor to the future of embodied interaction.
Research Focus
Key Achievements
Top Papers
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- 2