Longitudinal Multimodal Profiling of Balance and Gait In Stroke Using EEG and Lower Limb Sensors: A Feasibility Study.
Overview
- Phase
- N/A
- Intervention
- Not specified
- Conditions
- Stroke
- Sponsor
- Tan Tock Seng Hospital
- Enrollment
- 30
- Locations
- 1
- Primary Endpoint
- EEG Activities
- Status
- Recruiting
- Last Updated
- last year
Overview
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.
Investigators
Eligibility Criteria
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
Outcomes
Primary Outcomes
EEG Activities
Time Frame: 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
Time Frame: 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 Outcomes
- Fugl Meyer Assessment for Lower Limbs(Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment))
- Modified Clinical Test for Sensory Interaction in Balance(Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment))
- 10-metre Walk Test(Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment))
- 6-minute Walk Test(Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment))
- Berg Balance Scale(Week 0 (baseline), 4 (1st follow-up assessment), 8 (last follow-up assessment))