EEG Data AnalysisNCT02787200
Identification of Time-invariant EEG Signals for Brain-Computer Interface
An observational study of EEG Data Analysis and Healthy Subjects, run by National Taiwan University Hospital at 1 site in Taiwan.
Trial summary
This study aims to identify various time-variant and time-invariant components of EEG signals using advanced signal processing techniques, such as machine learning. The investigators' ultimate goal is to develop universal or customised brain-computer interface that are stable across days or even years. Read more about this study
- Who is it for?
- Ages 20 to 40 yearsHealthy volunteers can take part
- Conditions the study is for
- EEG Data Analysis, Healthy Subjects
- How many people
- 50 participants
- Where
- 1 siteTaiwan
- Study dates
- May 2016to May 2017
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 40 years
- All sexes
- Healthy volunteers accepted
- Adult
Study population: Healthy volunteers that understands Mandarin instructions.
Who may be able to join
None listed.
Who cannot join
- Severe vision disorders which prevent volunteers to recognize instructions on the screen
- Severe psychiatric disorders
- Severe sleep disorders which keep volunteers awake for two hours
- Volunteers with claustrophobia
- Patients who underwent stroke and brain surgery
- Patients with neuromuscular diseases
Trial locations and contacts
1 site in 1 country.
Taiwan1 site, 1 recruiting
- Recruiting
National Taiwan University Hospital
Taipei, Taipei, 10002
Tsung-Ren Huang, 886-2-3366-3104, trhuang@ntu.edu.tw
About this study
This study aims to identify various time-variant and time-invariant components of EEG signals using advanced signal processing techniques, such as machine learning. The investigators' ultimate goal is to develop universal or customised brain-computer interface that are stable across days or even years.
- Conditions
- EEG Data Analysis, Healthy Subjects
- Keywords
- electroencephalogram (EEG),Human brain,Brain-Computer Interface
What is being measured
The primary outcome is the main question the study is designed to answer.
Time invariant components of EEG signals
Measured: One month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Jun 2016 (estimated)
- Study startMay 2016
- Primary completionMay 2017 (estimated)
- Study completionMay 2017 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for EEG Data AnalysisStudies of the same condition, open and under way.
- More trials run by National Taiwan University HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Time perspective
- Cross-sectional
- Enrolment
- 50 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Taiwan University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Tsung-Ren Huang, Principal investigator, National Taiwan University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02787200
- Sponsor's protocol ID
- 201604024RIND
- Status last verified
- Jun 2016
- First submitted
- 26 May 2016
- Last updated
- 8 Jun 2016
- Results posted
- No
- Data monitoring committee
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 Jun 2016. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Identification of Time-invariant EEG Signals for Brain-Computer Interface
- ClinicalTrials.gov ID
- NCT02787200
- Acronym / sponsor ID
- 201604024RIND
- Conditions
- EEG Data Analysis, Healthy Subjects
- Keywords
- electroencephalogram (EEG),Human brain,Brain-Computer Interface
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 50 participants (estimated)
- Lead sponsor
- National Taiwan University HospitalUniversity, hospital or other
- Study start
- May 2016
- Primary completion
- May 2017 (estimated)
- Study completion
- May 2017 (estimated)
- First posted
- 1 Jun 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to identify various time-variant and time-invariant components of EEG signals using advanced signal processing techniques, such as machine learning. The investigators' ultimate goal is to develop universal or customised brain-computer interface that are stable across days or even years.
Study design
- Time perspective
- Cross-sectional
Who may qualify
- Ages
- 20 to 40 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- Healthy volunteers that understands Mandarin instructions.
Key inclusion criteria (0 listed)
Key exclusion criteria (6 listed)
- Severe vision disorders which prevent volunteers to recognize instructions on the screen
- Severe psychiatric disorders
- Severe sleep disorders which keep volunteers awake for two hours
- Volunteers with claustrophobia
- Patients who underwent stroke and brain surgery
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Time invariant components of EEG signals
Time frame: One month
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Jun 2016.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Tsung-Ren Huang principal investigator
National Taiwan University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of EEG Data Analysis and Healthy Subjects, run by National Taiwan University Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 0 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 8 Jun 2016. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Tsung-Ren Huang (886-23366-3104, trhuang@ntu.edu.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time invariant components of EEG signals (time frame: One month). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Jun 2016.