[HTML][HTML] Brain–computer interfaces: the innovative key to unlocking neurological conditions
H Zhang, L Jiao, S Yang, H Li, X Jiang… - … Journal of Surgery, 2024 - journals.lww.com
Neurological disorders such as Parkinson's disease, stroke, and spinal cord injury can pose
significant threats to human mortality, morbidity, and functional independence. Brain …
significant threats to human mortality, morbidity, and functional independence. Brain …
A review on visible-light eye-tracking methods based on a low-cost camera
This paper is the first of a two-part study aiming at building a low-cost visible-light eye tracker
(ET) for people with amyotrophic lateral sclerosis (ALS). The whole study comprises several …
(ET) for people with amyotrophic lateral sclerosis (ALS). The whole study comprises several …
SSVEP-based Brain-Computer Interface Controlled Robotic Platform with Velocity Modulation
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have
been extensively studied due to many benefits, such as non-invasiveness, high information …
been extensively studied due to many benefits, such as non-invasiveness, high information …
Camera-based blink detection using 3d-landmarks
Working in front of the computer for long periods of time leads to exhaustion, fatigue and
high strain on the eyes. Often the natural eye blink activity is disturbed and the eyes do not …
high strain on the eyes. Often the natural eye blink activity is disturbed and the eyes do not …
Dictionary reduction in sparse representation-based classification of motor imagery EEG signals
Recently, sparse representation-based classification has turned into a successful technique
for motor imagery electroencephalogram signal analysis. In this approach, the data is …
for motor imagery electroencephalogram signal analysis. In this approach, the data is …
[PDF][PDF] Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals.
A Altameem, JS Sachdev, V Singh… - … Systems Science & …, 2022 - academia.edu
Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG)
headsets in the form of EEG signals; these signals can be recorded, processed and …
headsets in the form of EEG signals; these signals can be recorded, processed and …
A Hardware-Based Configurable Algorithm for Eye Blink Signal Detection Using a Single-Channel BCI Headset
Eye blink artifacts in electroencephalographic (EEG) signals have been used in multiple
applications as an effective method for human–computer interaction. Hence, an effective …
applications as an effective method for human–computer interaction. Hence, an effective …
A Dataset and Post-Processing Method for Pointing Device Human-Machine Interface Evaluation/Un Conjunto de Datos y Metodo de Post-Procesamiento para …
The evaluation of human-machine interfaces (HMI) requires quantitative metrics to define
the ability of a person to effectively achieve their goals using the HMI. In particular, for …
the ability of a person to effectively achieve their goals using the HMI. In particular, for …
A Dataset and Post-Processing Method for Pointing Device Human-Machine Interface Evaluation
The evaluation of human-machine interfaces (HMI) requires quantitative metrics to define
the ability of a person to effectively achieve their goals using the HMI. In particular, for …
the ability of a person to effectively achieve their goals using the HMI. In particular, for …
A Novel Eeg Classification Method for Quantifying Kinematic Parameters
D Collins - 2023 - preprints.org
In recent years, low frequency (LF) electroencephalogram (EEG) signals have been
decoded to obtain kinematic trajectories with the aim of achieving closed loop natural …
decoded to obtain kinematic trajectories with the aim of achieving closed loop natural …