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| Name | Class |
|---|---|
| Institute for Infocomm Research | OTHER |
| Nanyang Technological University | OTHER |
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One-third of patients who had stroke suffered persistent disabilities, and upper limb (UL) motor impairment is one of the main disabilities. Recent clinical studies had been conducted using non-invasive EEG-based BCI via motor imagery, for post-stroke rehabilitation, yielded motor improvement of 7.2 on the Fugl-Meyer Motor Assessment (FMA-UE)score in chronic stroke patients that is significantly better than standard care. However, all the stroke patients underwent the same "one-size-fits-all" treatment option involving all six different activities of daily living (ADL)-oriented tasks regardless of their impairment or ability.
Investigators hypothesize that precision personalized stroke rehabilitation intervention that is tailored to the patient hold more promise than a "one-size-fits-all" stroke rehabilitation strategy.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| MBCI-SR | Experimental | BCI based robotic rehabilitation works by detecting the motor intent of the user from Electroencephalogram signals to drive rehabilitation assisted by the soft robotics gloves. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| MBCI-SR | Device | Participants will be asked to wear and EEG+NIRS cap and a soft robotic glove on their stroke-impaired hand. The participant will be instructed to ask to imagine to picture moving the stroke-imparied hand in the mind. The brain signal (EEG and NIRS data) will be recorded as a reference. When the participant pictures this move again, upon detection of such imagined move by MBCI-SR system, the glove will be activated and assists the participants to perform a specific upper limb task based on individual ability. There are six different activities of daily living (ADL)-oriented tasks enacted through a virtual arm and virtual objects, which formed the visual feedback for the participants. These tasks include scanning goods, moving an object upward to a cabinet, using two hands to move a towel, pouring of water into a cup, eating action and fine motor movement of picking up a small block using two fingers. Training intensity is 1.5 hours for 3 times a week for 6 weeks, a total of 18 sessions. |
| Measure | Description | Time Frame |
|---|---|---|
| Fugl-Meyer score of upper limb | a measure for upper extremity, movement coordination and reflex action. | Baseline |
| Fugl-Meyer score of upper limb | a measure for upper extremity, movement coordination and reflex action. | at week 4 (mid point) |
| Fugl-Meyer score of upper limb | a measure for upper extremity, movement coordination and reflex action. | at week 6 (completion of intervention) |
| Fugl-Meyer score of upper limb | a measure for upper extremity, movement coordination and reflex action. | at week 12 (at 3 month post intervention) |
| Fugl-Meyer score of upper limb | a measure for upper extremity, movement coordination and reflex action. | at week 24 (at 6 month post intervention) |
| Measure | Description | Time Frame |
|---|---|---|
| Action Research Arm Test | A measure for upper extremity functioning, such as dexterity and motor coordination, the key components in performing ADLs | Baseline |
| Action Research Arm Test | A measure for upper extremity functioning, such as dexterity and motor coordination, the key components in performing ADLs |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Chloe Lauha Chung, PhD | Contact | +65 6357 8305 | chloe_lh_chung@ttsh.com.sg | |
| Kai Keng Ang, PhD | Contact | +65 6408 2000 | kkang@i2r.a-star.edu.sg |
| Name | Affiliation | Role |
|---|---|---|
| Chloe Lauha Chung, PhD | Tan Tock Seng Hospital | Principal Investigator |
| Kai Keng Ang | Institute for Infocomm Research | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Tan Tock Seng Hospital Rehabilitation Centre | Recruiting | Singapore | 569766 | Singapore |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 18835541 | Background | Daly JJ, Wolpaw JR. Brain-computer interfaces in neurological rehabilitation. Lancet Neurol. 2008 Nov;7(11):1032-43. doi: 10.1016/S1474-4422(08)70223-0. Epub 2008 Oct 2. | |
| 24756025 | Result | Ang KK, Chua KS, Phua KS, Wang C, Chin ZY, Kuah CW, Low W, Guan C. A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke. Clin EEG Neurosci. 2015 Oct;46(4):310-20. doi: 10.1177/1550059414522229. Epub 2014 Apr 21. |
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Share the study protocol, clinical study report and results
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| ID | Term |
|---|---|
| D020521 | Stroke |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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|
| at week 12 (at 3 months post intervention) |
| Action Research Arm Test | A measure for upper extremity functioning, such as dexterity and motor coordination, the key components in performing ADLs | at week 24 ( at 6 months post intervention) |
| 25120465 | Result | Ang KK, Guan C, Phua KS, Wang C, Zhou L, Tang KY, Ephraim Joseph GJ, Kuah CW, Chua KS. Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke. Front Neuroeng. 2014 Jul 29;7:30. doi: 10.3389/fneng.2014.00030. eCollection 2014. |
| 32248089 | Result | Cheng N, Phua KS, Lai HS, Tam PK, Tang KY, Cheng KK, Yeow RC, Ang KK, Guan C, Lim JH. Brain-Computer Interface-Based Soft Robotic Glove Rehabilitation for Stroke. IEEE Trans Biomed Eng. 2020 Dec;67(12):3339-3351. doi: 10.1109/TBME.2020.2984003. Epub 2020 Nov 19. |
| 22208123 | Result | Ang KK, Guan C, Chua KS, Ang BT, Kuah CW, Wang C, Phua KS, Chin ZY, Zhang H. A large clinical study on the ability of stroke patients to use an EEG-based motor imagery brain-computer interface. Clin EEG Neurosci. 2011 Oct;42(4):253-8. doi: 10.1177/155005941104200411. |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |