Stroke
Conditions
Keywords
Electroencephalographic (EEG), Brain Computer Interfaces
Brief summary
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.
Detailed description
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.
Interventions
Assessments and questionnaires to quantify cortical and motor activities using portable EEG and lower limb sensors during dynamic balance and gait activities.
Sponsors
Nanyang Technological University
Tan Tock Seng Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
21 Years to 85 Years
Healthy volunteers
No
Inclusion criteria
* First-ever clinical stroke (ischaemic or haemorrhagic) confirmed by admitting doctors brain imaging * Age 21 to 85 years * At least ≥ 30 days post-stroke * Gait impairments related to stroke * Functional ambulation category -6 levels (Mehrholz et al, 2007): FAC ≥ 4, i.e. able to ambulate independently on level surface but requires supervision to negotiate (e.g. stairs, inclines, non-level surfaces). * Montreal Cognitive Assessment (MoCA) score \> 21 (Nasreddine et al., 2005) * Able to understand study instructions and requirements
Exclusion criteria
* Non-stroke related causes of gait impairment * Medical conditions incompatible with research participation: uncontrolled medical illnesses (hypertension or diabetes, ischaemic heart disease, congestive heart failure, bronchial asthma, severe /untreated depression, agitation, end stage renal/liver/heart/lung failure, dialysis, unresolved cancers e.g.,), active seizures within 3 months * Anticipated life expectancy of \< 6 months * On subcutaneous or oral anti-coagulation * Local factors potentially worsened by gait training: joint and muscle pains * Lower limb pain VAS \>4/10, active lower limb fractures or arthritis, fixed leg contractures, severe peripheral vascular disease, organomegaly or aortic aneurysms * Active unhealed skin wounds or inflammatory skin conditions over trunk and lower limbs, * Severe visual impairment or visual neglect affecting navigation * Known allergy to EEG gel (Recoverix) * Presence of craniectomy skull defect * Resident of nursing home or overseas country which may compromise attendance at research site * Pregnant or lactating females
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| EEG Activities | Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment) | To record EEG and EOG data from 64-Ch ActiCap EEG cap and electrode |
| Goniometers | Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment) | 7 sensors to measure 2-axis joint angles at bilateral Hip, Knee and Ankle |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Modified Clinical Test for Sensory Interaction in Balance | Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment) | Assess complex sensory system to assist in determining which sensory system the individual relies upon (visual, somatosensory, vestibul) |
| Fugl Meyer Assessment for Lower Limbs | Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment) | Change in Fugl Meyer Motor Assessment score in the affected arm, minimum: 0, maximum: 66 with higher scores indicating greater levels of mobility function |
| 6-minute Walk Test | Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment) | Determine the functional exercise capacity |
| 10-metre Walk Test | Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment) | To assess walking speed over a short distance |
| Berg Balance Scale | Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment) | To assess functional balance |
Countries
Singapore
Contacts
Primary ContactLow Ai Mei Jaclyn
Outcome results
None listed