Stroke
Conditions
Keywords
Brain-computer integration
Brief summary
This research aims to integrate and develop a novel Brain-Computer Interface (BCI) controlled soft robotic glove, evaluate the ability of the glove in achieving common hand grasping postures and to assess the efficacy of the glove in assisting stroke patients with completing functional tasks. The BCI-controlled soft robotic glove utilizes patients' user intent to deliver specific electroencephalographic patterns that can trigger robot-assisted hand movement to the affected hand.
Detailed description
Hand motor impairment is very common after a stroke. These impairments include difficulty moving and coordinating the hands and fingers, which inhibits stroke patients from being able to perform daily functional tasks independently, resulting in a reduced quality of life. More than half of people with upper limb impairment after stroke will still have problems many months to years after their stroke. Therefore, improving hand function is a core element of rehabilitation. Many possible interventions have been developed; these may involve different exercises or training, specialist equipment or techniques, or they could take the form of a drug (pill or injection) given to help hand movement. There is limited evidence that suggests the following interventions may be effective: constraint-induced movement therapy, mental practice, mirror therapy,interventions for sensory impairment, virtual reality and a relatively high dose of repetitive task practice. Current hand rehabilitation robotic devices are typically driven by rigid linkages or joints, which subject the patient's fingers into a single plane of motion that will feel unnatural and uncomfortable. On top of that,these devices belong to the class of continuous passive motion (CPM) devices that only promote hand range-of-motion, but do not require the patient to play a semi-active role in performing the hand exercises. Furthermore, there is a huge demand for solutions assisting stroke patients with using the densely paralyzed hand to perform activities of daily living (ADL) in real life, which is not available at present. Most of the hand rehabilitation robotic devices available in the market cannot assist paralyzed hand to carry out ADL. To develop an assistive device to solve this unmet need, we decided to combine BCI technology with the wearable soft robotic glove, which enables actuation of paralyzed hand by motor imagery.
Interventions
DEVICEBCI Robot Assisted Hand Therapy
18 sessions (3 times per week for a total of 6 weeks) of 1.5 hours each training (60 minutes of BCI Robot and 30 minutes of the standard hand therapy). Session 1-3. Peg game: Lateral movement of gears/cups Session 4-6. Moving cups onto a shelf: Elevation process for the arm, small cups to be used. Session 7-9. Carrying of basket: Heavier load to be used, patient to hold the basket by the handles at the side, not by its base. Session 10-12. Opening bottle + pouring into a cup: Training of ADL Session 13-15. Eating: Use of a modified spoon to train ADL Session 16-18. Box and blocks: Precise index finger and thumb control
DEVICECPM Robot Assisted Hand Therapy
18 sessions (3 times per week for a total of 6 weeks) of 1.5 hours each training (60 minutes of Passive Robot and 30 minutes of the standard hand therapy).The procedure will include the following: Session 1-18: Continuous passive motion
Sponsors
National University of Singapore
Agency for Science, Technology and Research
National University Hospital, Singapore
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DEVICE_FEASIBILITY
Masking
SINGLE (Outcomes Assessor)
Masking description
The blinding will be carried out in such a way that the therapist will provide conventional therapy and assess the arm function without knowing the group that the patients belong to. The BCI Robot and Passive Robot will be administered by other study team member. A third party study team member not participating in the intervention will keep the log book which contains information regarding patients study ID and group. Randomization codes will be broken when all interventional and follow-up sessions were completed or when the patient decides to quit participation. The third party team member will unmask according to PI's request in this occasion.
Intervention model description
A randomization stratification method, with a computer generated random sequence will be used. Subjects will be grouped in strata according to their Fugl-Meyer scores(0-28 vs 29-45) and randomized separately according to a block randomization to receive either of following treatments:(1) Treatment A: 18 sessions for 6 weeks of 60 minutes of passive robot-assisted hand therapy+ 30 minutes of standard hand therapy.(2) Treatment B: 18 sessions for 6 weeks of 60 minutes of BCI controlled robot-assisted hand therapy + 30 minutes of standard hand therapy.
Eligibility
Sex/Gender
ALL
Age
55 Years to 90 Years
Healthy volunteers
No
Inclusion criteria
* Aged 55-90 years regardless of lesion size, race * History of stroke less than 3 months prior to participation * Stroke type: ischemic or haemorrhagic * Fugl-Meyer motor score (FM score) of upper extremity impairment of 0-45 out of a maximum score of 66 on the Fugl-Meyer assessment scale * Ability to pay attention and maintain supported sitting for 1.5 hours continuously * Lack of or poor hand mobility (Medical Research Council Grade ≤ 2/5) * Able to give own consent * Able to comprehend and follow commands (Abbreviated Mental Test equal or more than 7) * Fulfil BCI resting brain states on initial screening. * Unilateral upper limb impairment
Exclusion criteria
* Recurrent clinical stroke * Functional status: severe aphasia or inattention, unstable medical conditions which may affect participation (e.g. unresolved sepsis, postural hypotension) or anticipated life expectancy of \<1 year due to malignancy or neurodegenerative disorder) * Hemispatial neglect (visual or sensory) or severe visual impairment despite visual aids * History of severe depression or active psychiatric disorder * Skull defect or previous cranial surgery as this would affect physical fit of EEG cap interface * Local arm factors: severe spasticity Modified Ashworth scale \>1+ in any region, fixed joint contractures or joint replacements, patients with poor skin conditions which would contraindicate repetitive arm training, upper limb pain impeding movements with visual analogue scale (VAS score) \>4/10, other conditions ensuing upper limb weakness, skull defect, polydactyly or amputation of fingers, and allergy to electrodes or adhesive gel
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Action Research Arm Test | 30 minutes | It assesses a client's ability to handle objects differing in size, weight and shape and therefore can be considered to be an arm-specific measure of activity limitation |
| Fugl-Meyer Assessment | 20 minutes | It is designed to assess motor functioning, balance, sensation and joint functioning. |
| Grip Strength Test | 5 minutes | The purpose of this test is to measure the maximum isometric strength of the hand and forearm muscles. |
Countries
Singapore
Outcome results
None listed