Andreea Ioana Sburlea

About

Andreea Ioana Sburlea is a leading researcher in non-invasive brain-computer interfaces (BCIs), with a focus on restoring motor function for individuals with paralysis or spinal cord injury. Her work centers on decoding voluntary arm and hand movements from low-frequency EEG signals, aiming to enable natural, continuous control of robotic arms and neuroprostheses. A key contribution is the development of frameworks that simultaneously decode movement intention and error-related potentials (ErrPs)—the brain’s response to mistakes—allowing BCIs to adapt and improve in real time. Her 2020 paper on continuous EEG decoding of arm movement has garnered 87 citations, while her 2019 study on online asynchronous ErrP detection during robot control has 76 citations, underscoring their impact. She also led the ERC-funded project “Feel Your Reach,” which established foundational methods for continuously detecting goal-directed movements and error processing to gate kinesthetic feedback. By using machine learning to reveal population vectors from non-invasive signals, Sburlea bridges the gap between invasive and non-invasive BCI control, bringing intuitive, closed-loop neuroprostheses closer to clinical reality.

Research Focus

Key Achievements

Top Papers

1. 1
   Continuous low-frequency EEG decoding of arm movement for closed-loop, natural control of a robotic arm

   87 citations · 2020
2. 2
   Online asynchronous decoding of error-related potentials during the continuous control of a robot

   76 citations · 2019
3. 3
   Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control

   22 citations · 2022
4. 4
   Using machine learning to reveal the population vector from EEG signals

   20 citations · 2020
5. 5
   Towards non-invasive brain-computer interface for hand/arm control in users with spinal cord injury

   8 citations · 2018

Key Collaborators

Contact & Links