Balance and gait recovery is a critical aspect of post-stroke motor rehabilitation. Researchers have effectively utilized EEG to investigate different aspects of lower limb motor control, however there are several technical challenges in the existing brain computer interface (BCI) motor profiling. The study aims to test the EEG-BCI system to see if it's effective in understanding the balance and walking patterns of post-stroke populations.
Brain Computer Interface represent a groundbreaking field at the crossroads of neuroscience and engineering, serving as a direct communication link between the human brain and computer system. Despite advancements in BCI technology, the electrocortical oscillations during human walking remain relatively unexplored, providing an opportunity for pioneering investigations. The research highlights the feasibility of using EEG to decode neural patterns associated with various functions and aims to contribute to existing knowledge by using advanced EEG-based techniques to predict balance and gait patterns with the ultimate goal of tailoring rehabilitation approaches to individual patient needs.
Study Type
OBSERVATIONAL
Enrollment
30
Assessments and questionnaires to quantify cortical and motor activities using portable EEG and lower limb sensors during dynamic balance and gait activities.
Tan Tock Seng Hospital
Singapore, Singapore, Singapore
RECRUITINGEEG Activities
To record EEG and EOG data from 64-Ch ActiCap EEG cap and electrode
Time frame: Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment)
Goniometers
7 sensors to measure 2-axis joint angles at bilateral Hip, Knee and Ankle
Time frame: Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment)
Fugl Meyer Assessment for Lower Limbs
Change in Fugl Meyer Motor Assessment score in the affected arm, minimum: 0, maximum: 66 with higher scores indicating greater levels of mobility function
Time frame: Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment)
Berg Balance Scale
To assess functional balance
Time frame: Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment)
Modified Clinical Test for Sensory Interaction in Balance
Assess complex sensory system to assist in determining which sensory system the individual relies upon (visual, somatosensory, vestibul)
Time frame: Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment)
10-metre Walk Test
To assess walking speed over a short distance
Time frame: Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment)
6-minute Walk Test
Determine the functional exercise capacity
Time frame: Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment)
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.