Multimodal EEG and NIRS-based BCI With Assistive Soft Robotics for Stroke (MBCI-SR)

Stroke Clinical Trial

— MBCI-SR  

Official title:

Multimodal EEG and NIRS-based BCI With Assistive Soft Robotics for Stroke

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05642299
• Other study ID #: 2021/00715
• Status: Recruiting
• Phase: N/A
• Start date: December 1, 2022
• Est. completion date: December 14, 2023

Study information

• Verified date: December 2022
• Source: Tan Tock Seng Hospital
• Contact: Chloe Lauha Chung, PhD
• Phone: +65 6357 8305
• Email: chloe_lh_chung[@]ttsh.com.sg
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

Description:

1. To address the "one-size-fits-all" stroke rehabilitation strategy, RRIS will develop an Ability data-driven personalized stroke rehabilitation based on the stroke patient's UL impairment and motor ability, by first matching 6 UL tasks in RRIS Ability Database with the 6 ADL tasks of the BCI-SR Intervention via similarity indices. A personalized subset of ADL tasks treatment options is then generated by a data-driven recommendation based on the patient's ability, movement pattern of the treatment option and the normative data from the RRIS Ability Database. A multi-modal BCI is proposed to perform EEG subject-specific calibration using Near-infrared spectroscopy, NIRS to ensure motor imagery compliance.

2. stroke subjects with UL impairments (score 11-45 on the FMA-UE) will be recruited to undergo the UL tasks assessment at RRIS. They will then undergo the personalized stroke rehabilitation using the Multimodal EEG and NIRS-based BCI with Soft Robotic therapy for 1.5 hour over 6 weeks, 3 times a week. The effectiveness of the personalized stroke rehabilitation can then be retrospectively compared to the use of "one-size-fits-all" ADL tasks in the previous clinical trial.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 10
• Est. completion date: December 14, 2023
• Est. primary completion date: September 14, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 50 Years to 80 Years

Eligibility

Inclusion Criteria:

• first ever stroke prior to clinical trial

• Fugl-Meyer Assessment scale of upper extremity impairment of 11-45 out of a maximum score of 66

• ability to give own consent

• ability to pay attention and maintain supported sitting for 1.5 hours continuously

• able to comprehend and follow commands

• fulfils BCI resting brain states on initial screening

• unilateral upper limb impairment

Exclusion Criteria:

• recurrent stroke

• inability to follow command and sit upright for 1.5 hours

• hemi-spatial neglect

• spasticity assessed by Modified Ashworth Scale more than 2/4

• History of Epilepsy

• Fixed contracture / deformity of finger joints

• upper limb pain impeding movements with visual analogy scale > 4/10

• Severe aphasia or cognitive impairment despite visual aids

• other conditions ensuing upper limb weakness

• poor skin conditions

• skull defect that might affect EEG or NIRS reading

• allergy to electrodes or adhesive gel

• significant vision and hearing impairment affecting participation

• Pregnant women

Related Conditions & MeSH terms

• Stroke

Intervention

Device:
• MBCI-SR
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.

Locations

Country	Name	City	State
Singapore	Tan Tock Seng Hospital Rehabilitation Centre	Singapore

Sponsors (3)

Lead Sponsor	Collaborator
Tan Tock Seng Hospital	Institute for Infocomm Research, Nanyang Technological University

Country where clinical trial is conducted

Singapore, 

References & Publications (5)

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 — View Citation

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: 10.1177/1550059 — View Citation

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. F — View Citation

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 — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Fugl-Meyer score of upper limb	a measure for upper extremity, movement coordination and reflex action.	Baseline
Primary	Fugl-Meyer score of upper limb	a measure for upper extremity, movement coordination and reflex action.	at week 4 (mid point)
Primary	Fugl-Meyer score of upper limb	a measure for upper extremity, movement coordination and reflex action.	at week 6 (completion of intervention)
Primary	Fugl-Meyer score of upper limb	a measure for upper extremity, movement coordination and reflex action.	at week 12 (at 3 month post intervention)
Primary	Fugl-Meyer score of upper limb	a measure for upper extremity, movement coordination and reflex action.	at week 24 (at 6 month post intervention)
Secondary	Action Research Arm Test	A measure for upper extremity functioning, such as dexterity and motor coordination, the key components in performing ADLs	Baseline
Secondary	Action Research Arm Test	A measure for upper extremity functioning, such as dexterity and motor coordination, the key components in performing ADLs	at week 12 (at 3 months post intervention)
Secondary	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)