EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution

EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution

This paper presents an EEG-based brain-computer interface system for classifying eleven motor imagery (MI) tasks within the same hand. The proposed system utilizes the Choi-Williams time-frequency distribution (CWD) to construct a time-frequency representation (TFR) of the EEG signals. The construct...

Full description

Bibliographic Details
Main Authors: Rami Alazrai, Hisham Alwanni, Yara Baslan, Nasim Alnuman, Mohammad I. Daoud
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Sensors
Subjects:
motor imagery
Choi-Williams time-frequency distribution
electroencephalography
time-frequency features
hierarchical classification
support vector machines
subject-independent analysis
Online Access:https://www.mdpi.com/1424-8220/17/9/1937

Similar Items

Similar Items