Motor imagery (MI) signals recorded by electroencephalography provide the most practical basis for conceiving brain-computer interfaces (BCI). These interfaces offer a high degree of freedom. This helps people with motor disabilities communicate with...
Biomedical physics & engineering express
Dec 30, 2022
More recently, a number of studies show the interest of the use of the Riemannian geometry in EEG classification. The idea is to exploit the EEG covariance matrices, instead of the raw EEG data, and use the Riemannian geometry to directly classify th...
Computer methods and programs in biomedicine
Dec 25, 2022
BACKGROUND: Incorporating the time-frequency localization properties of Gabor transform (GT), the complexity understandings of convolutional neural network (CNN), and histogram of oriented gradients (HOG) efficacy in distinguishing positive peaks can...
Achieving an efficient and reliable method is essential to interpret a user's brain wave and deliver an accurate response in biomedical signal processing. However, EEG patterns exhibit high variability across time and uncertainty due to noise and it ...
Mathematical biosciences and engineering : MBE
Dec 9, 2022
This paper presents a novel teleoperation system using Electroencephalogram (EEG) to control the motion of a wheeled mobile robot (WMR). Different from the other traditional motion controlling method, the WMR is braked with the EEG classification res...
IEEE journal of biomedical and health informatics
Dec 8, 2022
OBJECTIVE: Brain-computer interfaces (BCIs) have been used in two-dimensional (2D) navigation robotic devices, such as brain-controlled wheelchairs and brain-controlled vehicles. However, contemporary BCI systems are driven by binary selective contro...
To enhance the treatment of motor function impairment, patients' brain signals for self-control as an external tool may be an extraordinarily hopeful option. For the past 10 years, researchers and clinicians in the brain-computer interface (BCI) fiel...
Neurorehabilitation and neural repair
Nov 25, 2022
The development of brain-computer interface-controlled exoskeletons promises new treatment strategies for neurorehabilitation after stroke or spinal cord injury. By converting brain/neural activity into control signals of wearable actuators, brain/ne...
Brain-computer interfaces (BCIs) have been widely employed to identify and estimate a user's intention to trigger a robotic device by decoding motor imagery (MI) from an electroencephalogram (EEG). However, developing a BCI system driven by MI relate...
Brain-computer interfaces (BCIs) have achieved significant success in controlling external devices through the Electroencephalogram (EEG) signal processing. BCI-based Motor Imagery (MI) system bridges brain and external devices as communication tools...