A review of the role of machine learning techniques towards brain–computer interface applications
S Rasheed - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
This review article provides a deep insight into the Brain–Computer Interface (BCI) and the
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …
kNN and SVM classification for EEG: a review
This paper review the classification method of EEG signal based on k-nearest neighbor
(kNN) and support vector machine (SVM) algorithm. For instance, a classifier learns an input …
(kNN) and support vector machine (SVM) algorithm. For instance, a classifier learns an input …
An intelligent neuromarketing system for predicting consumers' future choice from electroencephalography signals
Abstract Neuromarketing utilizes Brain-Computer Interface (BCI) technologies to provide
insight into consumers responses on marketing stimuli. In order to achieve insight …
insight into consumers responses on marketing stimuli. In order to achieve insight …
A deep learning approach for motor imagery EEG signal classification
Over the last few decades, the use of electroencephalography (EEG) signals for motor
imagery based brain-computer interface (MI-BCI) has gained widespread attention. Deep …
imagery based brain-computer interface (MI-BCI) has gained widespread attention. Deep …
Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review
Support vector machines (SVMs) are widely used classifiers for detecting physiological
patterns in human–computer interaction (HCI). Their success is due to their versatility …
patterns in human–computer interaction (HCI). Their success is due to their versatility …
Identifying COVID-19 by using spectral analysis of cough recordings: a distinctive classification study
N Melek Manshouri - Cognitive neurodynamics, 2022 - Springer
Sound signals from the respiratory system are largely taken as tokens of human health.
Early diagnosis of respiratory tract diseases is of great importance because, if delayed, it …
Early diagnosis of respiratory tract diseases is of great importance because, if delayed, it …
General model for best feature extraction of EEG using discrete wavelet transform wavelet family and differential evolution
Wavelet family and differential evolution are proposed for categorization of epilepsy cases
based on electroencephalogram (EEG) signals. Discrete wavelet transform is widely used in …
based on electroencephalogram (EEG) signals. Discrete wavelet transform is widely used in …
Analysis of human gait using hybrid EEG-fNIRS-based BCI system: a review
Human gait is a complex activity that requires high coordination between the central nervous
system, the limb, and the musculoskeletal system. More research is needed to understand …
system, the limb, and the musculoskeletal system. More research is needed to understand …
BCI-based consumers' choice prediction from EEG signals: an intelligent neuromarketing framework
Neuromarketing relies on Brain Computer Interface (BCI) technology to gain insight into how
customers react to marketing stimuli. Marketers spend about $750 billion annually on …
customers react to marketing stimuli. Marketers spend about $750 billion annually on …
Using psychophysiological sensors to assess mental workload during web browsing
Knowledge of the mental workload induced by a Web page is essential for improving users'
browsing experience. However, continuously assessing the mental workload during a …
browsing experience. However, continuously assessing the mental workload during a …