A Wearable Asynchronous Brain-Computer Interface Based on EEG-EOG Signals With Fewer Channels.
IEEE Trans Biomed Eng
; 71(2): 504-513, 2024 Feb.
Article
em En
| MEDLINE
| ID: mdl-37616137
ABSTRACT
OBJECTIVE:
Brain-computer interfaces (BCIs) have tremendous application potential in communication, mechatronic control and rehabilitation. However, existing BCI systems are bulky, expensive and require laborious preparation before use. This study proposes a practical and user-friendly BCI system without compromising performance.METHODS:
A hybrid asynchronous BCI system was developed based on an elaborately designed wearable electroencephalography (EEG) amplifier that is compact, easy to use and offers a high signal-to-noise ratio (SNR). The wearable BCI system can detect P300 signals by processing EEG signals from three channels and operates asynchronously by integrating blink detection.RESULT:
The wearable EEG amplifier obtains high quality EEG signals and introduces preprocessing capabilities to BCI systems. The wearable BCI system achieves an average accuracy of 94.03±4.65%, an average information transfer rate (ITR) of 31.42±7.39 bits/min and an average false-positive rate (FPR) of 1.78%.CONCLUSION:
The experimental results demonstrate the feasibility and practicality of the developed wearable EEG amplifier and BCI system.SIGNIFICANCE:
Wearable asynchronous BCI systems with fewer channels are possible, indicating that BCI applications can be transferred from the laboratory to real-world scenarios.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Interfaces Cérebro-Computador
/
Dispositivos Eletrônicos Vestíveis
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article