Automatic classification methods for detecting drowsiness using wavelet packet transform extracted time-domain features from single-channel EEG signal
S Chinara - Journal of neuroscience methods, 2021 - Elsevier
Background Detecting human drowsiness during some critical works like vehicle driving,
crane operating, mining blasting, etc. is one of the safeguards to prevent accidents. Among …
crane operating, mining blasting, etc. is one of the safeguards to prevent accidents. Among …
A machine learning approach to predicting pervious concrete properties: a review
This paper investigates the application of machine learning to predict the properties of
pervious concrete. Traditional methods like lab tests and formulas have limitations. Machine …
pervious concrete. Traditional methods like lab tests and formulas have limitations. Machine …
An optimized deep hybrid learning for multi-channel EEG-based driver drowsiness detection
Driver drowsiness is a severe issue that has contributed to numerous fatal accidents and
injuries. Thus, detecting driver drowsiness is an important task that has been the subject of …
injuries. Thus, detecting driver drowsiness is an important task that has been the subject of …
[HTML][HTML] A single-trial P300 detector based on symbolized EEG and autoencoded-(1D) CNN to improve ITR performance in BCIs
In this paper, we propose a breakthrough single-trial P300 detector that maximizes the
information translate rate (ITR) of the brain–computer interface (BCI), kee** high …
information translate rate (ITR) of the brain–computer interface (BCI), kee** high …
CCNSim: An artificial intelligence enabled classification, clustering and navigation simulator for Social Internet of Things
With the advent of the IoT technology stack and the need for information and process
ubiquity, social IoT (SIoT) is becoming popular to cater to intelligent and connected living …
ubiquity, social IoT (SIoT) is becoming popular to cater to intelligent and connected living …
Studies on electroencephalogram for upper limb rehabilitation
Upper limb movement decoding from electroencephalogram (EEG) signals is an emerging
field that has gained increasing attention over the past few years for its application in …
field that has gained increasing attention over the past few years for its application in …
A Comprehensive Survey on Rehabilitative Applications of Electroencephalogram in Healthcare
A set of therapeutic control required for persons suffering from or expected to suffer from
limitations in daily living activities is called rehabilitation which can restore or improve the …
limitations in daily living activities is called rehabilitation which can restore or improve the …
Internet of Things-Combined Deep Learning for Electroencephalography-Based E-Healthcare
Deep Learning (DL) is the most popular subset of machine learning, with many applications
in healthcare and other areas. On the other hand, electroencephalography has effectively …
in healthcare and other areas. On the other hand, electroencephalography has effectively …
[PDF][PDF] ONTOLOGY DRIVEN, ARTIFICIAL INTELLIGENCE BASED CAREER PLANNING SYSTEM FOR INDIVIDUALS
B AKTAŞ - 2024 - enstituois.sakarya.edu.tr
I sincerely thank my advisor, Assoc. Prof. Dr. Adem AKBIYIK for his valuable contributions
and leadership at every stage of my thesis and guiding me through my academic career. I …
and leadership at every stage of my thesis and guiding me through my academic career. I …
An Explainable Deep Learning Approach for EEG-Induced Motor Imagery Classification
Movement interpretation from the motor imagery (MI) signal of electroencephalogram (EEG)
is an emerging field that can potentially upgrade the quality of life of individuals with motor …
is an emerging field that can potentially upgrade the quality of life of individuals with motor …