Parallel genetic algorithm based common spatial patterns selection on time–frequency decomposed EEG signals for motor imagery brain-computer interface
T Luo - Biomedical Signal Processing and Control, 2023 - Elsevier
Since the nonlinear and non-stationary characteristics of electroencephalogram (EEG)
signals, motor imagery based brain-computer interface (MI-BCI) have problems of poor …
signals, motor imagery based brain-computer interface (MI-BCI) have problems of poor …
An evaluation model for children's foot & ankle deformity severity using sparse multi-objective feature selection algorithm
Foot & ankle deformity is a chronic disease with high incidence and is best treated in
childhood. However, the current diagnostic procedures rely on doctor's consultation and …
childhood. However, the current diagnostic procedures rely on doctor's consultation and …
[PDF][PDF] Assessment and application of EEG: A literature review
Advancements in neuroscience have enabled the collection and assessment of neurological
data to assist in the detection and treatment of several medical conditions as well as the …
data to assist in the detection and treatment of several medical conditions as well as the …
Selective regularized spatial features representation learning for motor imagery EEG based on alternating cascaded model
T Luo - Applied Soft Computing, 2024 - Elsevier
Feature representation plays a pivotal role in the decoding of motor imagery
electroencephalograph (MI-EEG) signals. Conventional spatial representations are often …
electroencephalograph (MI-EEG) signals. Conventional spatial representations are often …
Selective multi–view time–frequency decomposed spatial feature matrix for motor imagery EEG classification
T Luo - Expert Systems with Applications, 2024 - Elsevier
Decoding brain activity from non-invasive motor imagery electroencephalograph (MI-EEG)
has garnered significant attentions for brain-computer interface (BCI) and brain disorders …
has garnered significant attentions for brain-computer interface (BCI) and brain disorders …
Boosting the convergence of a ga-based wrapper for feature selection problems on high-dimensional data
High-dimensional data often need techniques, such as Feature Selection (FS), in order to
solve the curse of dimensionality problem. One of the most popular approaches to FS is …
solve the curse of dimensionality problem. One of the most popular approaches to FS is …
SACE scanning process assisted with ultrasonic vibration on quartz glass
Y Luo, H Tong, G Liu, T Wu, Y Li - Materials and Manufacturing …, 2022 - Taylor & Francis
Spark-assisted chemical engraving (SACE) is suitable to machine hard and brittle insulating
materials such as quartz glass; however, the processing efficiency is quite low for achieving …
materials such as quartz glass; however, the processing efficiency is quite low for achieving …
COR-MFS: A Correlation-Based Multi-Objective Feature Selection on EEG Signals
A Sutradhar, AA Bidgoli… - 2024 IEEE Congress on …, 2024 - ieeexplore.ieee.org
Feature selection is a crucial step in the model-building pipeline in machine learning (ML)
applications such as Electroencephalogram (EEG) signal processing, providing benefits on …
applications such as Electroencephalogram (EEG) signal processing, providing benefits on …