Vision-Based Feedback on Correct Sensor Placement in Medical Studies

This project is a collaboration between the RoPeRT research lab from Universidad de Zaragoza and Bitbrain.

Participants: Nerea Gallego, Carlos Plou, Luis Montesano, Ana C. Murillo, Eduardo Montijano.

Brief Description

This project presents a lightweight computer-vision system designed to help users correctly position a neuroheadband used for EEG data collection in medical studies and brain–robot interfaces. Using a simple webcam, the system analyzes facial landmarks and segments the headband to detect common placement errors—such as incorrect height or misalignment—and provides real-time visual feedback. 

Optimized for low-power devices like tablets or laptops, the system achieves 94% accuracy in identifying incorrect placements, ensuring reliable EEG recordings even when used by non-expert users. This technology enhances usability, reduces setup errors, and supports more accurate and accessible at-home health monitoring. 

• Publication: Gallego, N., Plou, C., Montesano, L., Murillo, A. C., & Montijano, E. (2024, November). Vision-Based Feedback on Correct Sensor Placement in Medical Studies. In 2024 7th Iberian Robotics Conference (ROBOT) (pp. 1-6). IEEE.
  https://ieeexplore.ieee.org/abstract/document/10796934.