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Trial Review
The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this
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Trial registered on ANZCTR
Registration number
ACTRN12624001471572
Ethics application status
Approved
Date submitted
25/11/2024
Date registered
18/12/2024
Date last updated
18/12/2024
Date data sharing statement initially provided
18/12/2024
Type of registration
Retrospectively registered
Titles & IDs
Public title
A longitudinal study to investigate the learning effect of virtual reality-based brain-computer interface training on motor imagery signals in unimpaired individuals
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Scientific title
The effect of longitudinal virtual reality mediated brain-computer interface (BCI) training on sensorimotor neuromodulation and BCI control in unimpaired individuals
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Secondary ID [1]
313458
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Nil known
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Universal Trial Number (UTN)
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Trial acronym
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Unimpaired individuals
335859
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Neurorehabilitation
335860
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Condition category
Condition code
Neurological
332439
332439
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0
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Studies of the normal brain and nervous system
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Physical Medicine / Rehabilitation
332440
332440
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0
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Other physical medicine / rehabilitation
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Neurological
332564
332564
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0
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Other neurological disorders
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Intervention/exposure
Study type
Interventional
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Description of intervention(s) / exposure
Virtual reality brain-computer interface (VR-BCI) Training
Seven healthy, right-handed volunteers (2 females, aged 24-40) participated in this study. None had any medical conditions like pregnancy, claustrophobia, drug addiction, or neurological diseases that could interfere with the tasks. Each person completed 15 training sessions, held on different days, with no more than three sessions per week.
All sessions were administered by one of the researcher from the team. All participants received exactly the same tasks throughout the intervention.
The study followed ethical guidelines, was approved by Griffith University’s research ethics board, and all participants gave written consent before joining.
During each session, participants sat comfortably while wearing an electroencephalogram (EEG) headset to measure brain activity and a virtual reality (VR) headset for the tasks. They practiced two types of mental exercises: imagining themselves walking or relaxing. Each session included three phases: calibration, cued-online with feedback, and using the system freely without cues. Breaks of 1-3 minutes were given between phases, depending on the participant's readiness. Each session, including setup, took about an hour and was conducted in Griffith University’s Physiotherapy Laboratory (G02_1.17).
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Intervention code [1]
330030
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Rehabilitation
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Intervention code [2]
330031
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Treatment: Devices
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Comparator / control treatment
No control group
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Control group
Uncontrolled
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Outcomes
Primary outcome [1]
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Change in the ability of the participant to control the brain-computer interface system.
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Assessment method [1]
339982
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Classification accuracy i.e., how accurately system predicts the imagined task by the users. Accuracy is determined at the end of each session by the researcher.
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Timepoint [1]
339982
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after the first three training sessions and last three training sessions
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Primary outcome [2]
339983
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Electroencephalogram (EEG) signal separability
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Assessment method [2]
339983
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Class discrimination
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Timepoint [2]
339983
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After first three training sessions and last three training sessions
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Primary outcome [3]
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Electroencephalogram (EEG) signal separability
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Assessment method [3]
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Test-train adaptation
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Timepoint [3]
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After first three training sessions and last three training sessions
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Secondary outcome [1]
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Correlation between classification accuracy and self-prediction
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Assessment method [1]
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Questionnaire. The Questionnaire was designed specifically for this study. Subjects were asked to fill out the questionnaire at each session and the classification accuracy (primary outcome 1) was determined at the end of each session. The correlation between classification accuracy and self-prediction was calculated for each subject at the end of the study (i.e., when each subject completed 15 sessions training).
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Timepoint [1]
442190
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At the start and end of each session
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Eligibility
Key inclusion criteria
Following factors were considered/recorded for selecting participants for the study:
1. Healthy with no prior illnesses,
2. Participants should have a normal or corrected-to-normal vision.
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
Yes
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Key exclusion criteria
Following factors were considered for rejecting a participant for the study:
1. Pregnancy
2. Claustrophobia
3. Drug addiction
4. Neurological diseases
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Study design
Purpose of the study
Treatment
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Allocation to intervention
Non-randomised trial
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Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
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Methods used to generate the sequence in which subjects will be randomised (sequence generation)
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Masking / blinding
Open (masking not used)
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Who is / are masked / blinded?
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Intervention assignment
Single group
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Other design features
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Phase
Not Applicable
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Type of endpoint/s
Efficacy
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Statistical methods / analysis
The number of participants for this study was determined based on prior studies in brain-computer interface (BCI) research and virtual reality (VR)-based rehabilitation, which typically involve small sample sizes (5–10 participants) for exploratory and longitudinal investigations. The focus was on feasibility and observing significant trends in learning motor imagery (MI) control over multiple sessions. Participants were recruited to represent a sufficient sample for detecting individual changes in BCI performance and sensorimotor neuromodulation through repeated measures analysis.
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Recruitment
Recruitment status
Completed
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Date of first participant enrolment
Anticipated
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Actual
2/03/2021
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Date of last participant enrolment
Anticipated
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Actual
24/03/2021
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Date of last data collection
Anticipated
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Actual
7/09/2021
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Sample size
Target
7
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Accrual to date
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Final
7
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Recruitment in Australia
Recruitment state(s)
QLD
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Funding & Sponsors
Funding source category [1]
317894
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Government body
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Name [1]
317894
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Queensland Motor Accident Insurance Commission (MAIC)
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Address [1]
317894
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Country [1]
317894
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Australia
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Primary sponsor type
University
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Name
Griffith University
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Address
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Country
Australia
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Secondary sponsor category [1]
320238
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None
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Name [1]
320238
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Address [1]
320238
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Country [1]
320238
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
316582
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Griffith University Human Research Ethics Committee
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Ethics committee address [1]
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https://www.griffith.edu.au/research/research-services/research-ethics-integrity/human/human-research-ethics-committee
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Ethics committee country [1]
316582
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Australia
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Date submitted for ethics approval [1]
316582
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24/02/2021
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Approval date [1]
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21/03/2021
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Ethics approval number [1]
316582
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GU ref no: 2021/170
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Summary
Brief summary
Rehabilitation is crucial for recovering motor functions after injuries like spinal cord injury (SCI) or stroke. Traditional methods often require a lot of manual effort from therapists, making them time-consuming and less effective for patients with limited or no motor control. Brain-computer interfaces (BCIs) offer a promising alternative by converting brain signals into commands that assist devices, enabling automated therapy without constant manual input. Our study focuses on training individuals, especially those new to BCIs, to use their imagination to control these systems in a virtual reality (VR) environment. This approach could make rehabilitation more efficient, engaging, and accessible for people with severe motor impairments.
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Trial website
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
138314
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Dr Malik Muhammad Naeem Mannan
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Address
138314
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Room 2.09, Building G02, Gold Coast Campus, Griffith University, 1 Parklands Dr, Southport QLD 4215
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Country
138314
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Australia
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Phone
138314
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+61 756780576
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Fax
138314
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Email
138314
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[email protected]
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Contact person for public queries
Name
138315
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Malik Muhammad Naeem Mannan
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Address
138315
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Room 2.09, Building G02, Gold Coast Campus, Griffith University, 1 Parklands Dr, Southport QLD 4215
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Country
138315
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Australia
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Phone
138315
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+61 756780576
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Fax
138315
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Email
138315
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[email protected]
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Contact person for scientific queries
Name
138316
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Malik Muhammad Naeem Mannan
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Address
138316
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Room 2.09, Building G02, Gold Coast Campus, Griffith University, 1 Parklands Dr, Southport QLD 4215
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Country
138316
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Australia
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Phone
138316
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+61 756780576
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Fax
138316
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Email
138316
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[email protected]
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Data sharing statement
Will the study consider sharing individual participant data?
Yes
Will there be any conditions when requesting access to individual participant data?
Persons/groups eligible to request access:
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Access to IPD can be requested by qualified researchers engaging in independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA).
Conditions for requesting access:
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What individual participant data might be shared?
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Raw de-identified electroencephalography data acquired at during the study.
What types of analyses could be done with individual participant data?
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Data will be made available for meta analyses and other scientific studies developing algorithms to improve brain-computer interfaces.
When can requests for individual participant data be made (start and end dates)?
From:
Data requests can be submitted starting 9 months after article publication and the data will be made accessible for up to 24 months. Extensions will be considered on a case-by-case basis.
To:
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Where can requests to access individual participant data be made, or data be obtained directly?
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Data can be obtained upon email request to the principal investigator. Please contact Dr Malik Muhammad Naeem Mannan by emailing
[email protected]
Are there extra considerations when requesting access to individual participant data?
No
What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
No additional documents have been identified.
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