Healthy Subjects Clinical Trial
Official title:
Identification of Time-invariant EEG Signals for Brain-Computer Interface
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.
Status | Recruiting |
Enrollment | 50 |
Est. completion date | May 2017 |
Est. primary completion date | May 2017 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | Both |
Age group | 20 Years to 40 Years |
Eligibility |
Exclusion criteria: 1. Severe vision disorders which prevent volunteers to recognize instructions on the screen 2. Severe psychiatric disorders 3. Severe sleep disorders which keep volunteers awake for two hours 4. Volunteers with claustrophobia 5. Patients who underwent stroke and brain surgery 6. Patients with neuromuscular diseases |
Time Perspective: Cross-Sectional
Country | Name | City | State |
---|---|---|---|
Taiwan | National Taiwan University Hospital | Taipei |
Lead Sponsor | Collaborator |
---|---|
National Taiwan University Hospital |
Taiwan,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Time invariant components of EEG signals | One month | No |
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