Clinical trial NCT03277508: Assistive Soft Robotic Glove Intervention Using Brain-Computer Interface for Elderly Stroke Patients
Official title: Assistive Soft Robotic Glove Intervention Using Brain-Computer Interface for Elderly Stroke Patients
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Stroke
Keywords: Brain-computer integration
Lead sponsor: National University Hospital, Singapore
Sponsor class: OTHER
Collaborators: name: National University of Singapore
name: Agency for Science, Technology and Research
First posted: 2017-09-11
Enrollment: 11
Sex: ALL
Minimum age (years): 55
Maximum age (years): 90
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
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.
Primary purpose: DEVICE_FEASIBILITY

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.

Eligibility criteria: 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

Primary outcomes:
measure: Action Research Arm Test
timeFrame: 30 minutes
measure: Fugl-Meyer Assessment
timeFrame: 20 minutes
measure: Grip Strength Test
timeFrame: 5 minutes
Secondary outcomes:
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: National University Hospital
Study officials:
affiliation: National University Hospital, Singapore
name: Jeong Hoon Lim
role: PRINCIPAL_INVESTIGATOR
References:
citation: F.Z. Low, H.K. Yap, J.H. Lim, F. Nasrallah, J.C.H. Goh, C.H. Yeow. Wearable Soft Robotics for Rehabilitation. 8th Asian Pacific Conference on Biomechanics 2015 (Sapporo).
citation: H.K. Yap, F. Nasrahllah, J.H. Lim, F.Z. Low, J.C.H. Goh, C.H. Yeow. MRC-Glove: A fMRI Compatible Soft Robotic Glove for Hand Rehabilitation Application, 14th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics (ICORR 2015).
citation: H.K. Yap, J.H. Lim, F. Nasrahllah, J.C.H. Goh, C.H. Yeow. A Soft Exoskeleton for Hand Assistive and Rehabilitation Application Page 8 using Pneumatic Actuators with Variable Stiffness, in IEEE Int. Conf. Robotics and Automation 2015.
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