[HTML][HTML] A state-of-the-art review of EEG-based imagined speech decoding
Currently, the most used method to measure brain activity under a non-invasive procedure is
the electroencephalogram (EEG). This is because of its high temporal resolution, ease of …
the electroencephalogram (EEG). This is because of its high temporal resolution, ease of …
A new one-dimensional testosterone pattern-based EEG sentence classification method
Electroencephalography (EEG) signals are crucial data to understand brain activities. Thus,
many papers have been proposed about EEG signals. In particular, machine learning …
many papers have been proposed about EEG signals. In particular, machine learning …
Neural decoding of Chinese sign language with machine learning for brain–computer interfaces
Limb motion decoding is an important part of brain-computer interface (BCI) research.
Among the limb motion, sign language not only contains rich semantic information and …
Among the limb motion, sign language not only contains rich semantic information and …
Aquila-eagle-based deep convolutional neural network for speech recognition using EEG signals
The conventional BCI system experiences several issues such as background noise
interference, lower precision rate and high cost. Hence, a novel speech recognition model …
interference, lower precision rate and high cost. Hence, a novel speech recognition model …
A Comparative Study of Traditional and Transformer-based Deep Learning Models for Multi-Class Eye Movement Recognition Using Collected Dataset
AA Masaoodi, HH Abbas… - … Conference on Advanced …, 2023 - ieeexplore.ieee.org
The study of eye movement recognition has emerged as a pivotal focus, particularly in fields
such as human-computer interaction, healthcare diagnostics, and adaptive technologies …
such as human-computer interaction, healthcare diagnostics, and adaptive technologies …
[PDF][PDF] Facultad de Ingeniería en Mecánica y Ciencias de la Producción
I en Mecánica, DAL Correa, FRS Tumbaco - 2023 - dspace.espol.edu.ec
Debido a que la comunicación oral es de suma importancia en el ámbito educativo, es
crucial mantener los niveles de ruido por debajo de los límites permitidos dentro como fuera …
crucial mantener los niveles de ruido por debajo de los límites permitidos dentro como fuera …
Neural speech decoding with magnetoencephalography
D Dash - 2021 - repositories.lib.utexas.edu
Severe brain damage or amyotrophic lateral sclerosis (ALS) may lead the patients to a
locked-in state where the patients are motorically paralyzed otherwise being cognitively …
locked-in state where the patients are motorically paralyzed otherwise being cognitively …
Brain Computer Interface-EEG based Imagined Word Prediction Using Convolutional Neural Network Visual Stimuli for Speech Disability
B Chinta, M Moorthi - 2022 - researchsquare.com
Abstract Brain Computer Interface (BCI) is one of the fast-growing technological trends,
which finds its applications in the field of the healthcare sector. In this work, 16 electrodes of …
which finds its applications in the field of the healthcare sector. In this work, 16 electrodes of …
Efficient Automatic Speech Recognition from EEG Signals Using Optimal Deep Learning Approach
MB Chinta - papers.ssrn.com
EEG speech recognition is vital in daily life. EEG signals relate brain dynamics and moods to
improve machine-human interactions. Speech recognition using EEG waves has been …
improve machine-human interactions. Speech recognition using EEG waves has been …