Marianne Severens
Papers
1
Total Citations
70
H-Index
1
About
Marianne Severens is a leading researcher in the fields of brain-computer interfaces (BCIs) and neurorehabilitation, with a particular focus on decoding sensorimotor rhythms during locomotion. Her most cited work, "Decoding Sensorimotor Rhythms during Robotic-Assisted Treadmill Walking for Brain Computer Interface (BCI) Applications" (2015, 70 citations), represents a pivotal contribution to the field. In this study, Severens demonstrated that neural signals associated with walking can be reliably decoded from electroencephalography (EEG) during robotic-assisted treadmill training, opening new possibilities for integrating BCIs into gait rehabilitation for patients with stroke and spinal cord injury. Her research bridges the gap between assistive robotics and neural control, offering a pathway toward more adaptive, patient-responsive rehabilitation technologies. By showing that sensorimotor rhythms remain detectable and classifiable during active walking with robotic support, Severens has helped lay the groundwork for closed-loop neuroprosthetic systems. Her work is widely cited by researchers developing non-invasive BCIs for motor recovery, and it continues to influence the design of next-generation rehabilitation devices that combine robotic assistance with real-time neural feedback.
Research Focus
Key Achievements
Top Papers
- 1