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

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

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.

Study Overview

• Status: Recruiting
• Conditions: Stroke
• Intervention / Treatment: Device: MBCI-SR

Detailed 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.

• Study Type: Interventional
• Enrollment (Anticipated): 10
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Chloe Lauha Chung, PhD; Phone Number: +65 6357 8305; Email: chloe_lh_chung@ttsh.com.sg
• Study Contact Backup: Name: Kai Keng Ang, PhD; Phone Number: +65 6408 2000; Email: kkang@i2r.a-star.edu.sg

Study Locations

• Singapore
  • Singapore, Singapore, 569766
    • Recruiting
    • Tan Tock Seng Hospital Rehabilitation Centre
    • Contact: Chloe Lauha Chung, PhD; Phone Number: 6357 8305; Email: Chloe_lh_chung@ttsh.com.sg

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 50 years to 80 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: MBCI-SR; 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.

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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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)

Secondary Outcome Measures

Outcome Measure	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	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)

Collaborators and Investigators

• Sponsor: Tan Tock Seng Hospital
• Collaborators: Nanyang Technological University; Institute for Infocomm Research
• Investigators: Principal Investigator: Chloe Lauha Chung, PhD, Tan Tock Seng Hospital; Principal Investigator: Kai Keng Ang, Institute for Infocomm Research

Publications and helpful links

General Publications

• 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.
• 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.
• 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.
• 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.
• 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.

Study record dates

Study Major Dates

• Study Start (Anticipated): December 1, 2022
• Primary Completion (Anticipated): September 14, 2023
• Study Completion (Anticipated): December 14, 2023

Study Registration Dates

• First Submitted: November 15, 2022
• First Submitted That Met QC Criteria: December 7, 2022
• First Posted (Estimate): December 8, 2022

Study Record Updates

• Last Update Posted (Estimate): December 8, 2022
• Last Update Submitted That Met QC Criteria: December 7, 2022
• Last Verified: December 1, 2022

More Information

Terms related to this study

• Keywords: Brain-Computer Interface; upper limb rehabilitation
• Additional Relevant MeSH Terms: Cardiovascular Diseases; Vascular Diseases; Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Stroke
• Other Study ID Numbers: 2021/00715

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No
• IPD Plan Description: Share the study protocol, clinical study report and results

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No