Identification of Time-invariant EEG Signals for Brain-Computer Interface

National Taiwan University

Status: Unknown

Conditions: Healthy Subjects; EEG Data Analysis

Study type: Observational

Funder types: Other

Identifiers

NCT02787200

201604024RIND

Details and patient eligibility

About

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.

Enrollment: 50 estimated patients

Sex: All

Ages: 20 to 40 years old

Volunteers: Accepts Healthy Volunteers

Inclusion and exclusion criteria

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