Applications of artificial intelligence− machine learning for detection of stress: a critical overview
Psychological distress is a major contributor to human physiology and pathophysiology, and
it has been linked to several conditions, such as auto-immune diseases, metabolic …
it has been linked to several conditions, such as auto-immune diseases, metabolic …
Znet: deep learning approach for 2D MRI brain tumor segmentation
Background: Detection and segmentation of brain tumors using MR images are challenging
and valuable tasks in the medical field. Early diagnosing and localizing of brain tumors can …
and valuable tasks in the medical field. Early diagnosing and localizing of brain tumors can …
[HTML][HTML] Machine learning, deep learning, and data preprocessing techniques for detecting, predicting, and monitoring stress and stress-related mental disorders …
Background Mental stress and its consequent mental health disorders (MDs) constitute a
significant public health issue. With the advent of machine learning (ML), there is potential to …
significant public health issue. With the advent of machine learning (ML), there is potential to …
ECG and EEG based detection and multilevel classification of stress using machine learning for specified genders: A preliminary study
A Hemakom, D Atiwiwat, P Israsena - Plos one, 2023 - journals.plos.org
Mental health, especially stress, plays a crucial role in the quality of life. During different
phases (luteal and follicular phases) of the menstrual cycle, women may exhibit different …
phases (luteal and follicular phases) of the menstrual cycle, women may exhibit different …
[HTML][HTML] Green EEG energy control robot for supporting bedfast patients
C Boonarchatong, M Ketcham - Energy Reports, 2023 - Elsevier
The objectives of this study were (1) to develop a prototype for controlling the movements of
a robot by using green electroencephalography (EEG) energy and (2) to test a prototype …
a robot by using green electroencephalography (EEG) energy and (2) to test a prototype …
Automated attention deficit classification system from multimodal physiological signals
Lack of attention, if it could not be taken care of and persists for a long time then may lead to
a severe issue. Analysis of Electroencephalogram (EEG) signals can effectively measure …
a severe issue. Analysis of Electroencephalogram (EEG) signals can effectively measure …
Machine learning, deep learning and data preprocessing techniques for detection, prediction, and monitoring of stress and stress-related mental disorders: a scoping …
This comprehensive review systematically evaluates Machine Learning (ML) methodologies
employed in the detection, prediction, and analysis of mental stress and its consequent …
employed in the detection, prediction, and analysis of mental stress and its consequent …
[HTML][HTML] Comparative analysis of dimensionality reduction techniques for EEG-based emotional state classification
SA Sadegh-Zadeh, N Sadeghzadeh… - American Journal of …, 2024 - pmc.ncbi.nlm.nih.gov
Objectives: The aim of this study is to evaluate the impact of various dimensionality reduction
methods, including principal component analysis (PCA), Laplacian score, and Chi-square …
methods, including principal component analysis (PCA), Laplacian score, and Chi-square …
KRAFS-ANet: A novel framework for EEG-based stress classification using channel selection and optimized ensemble stacking
Mental stress poses a widespread societal challenge, impacting daily routines and
contributing to severe health problems. The earlier studies have utilized …
contributing to severe health problems. The earlier studies have utilized …
Stress Detection and Audio-Visual Stimuli Classification from Electroencephalogram
Electroencephalogram (EEG) is the graphical representation of Brain's electrical activity.
Mental stress can be detected in many ways and EEG is one of them. Regular mental stress …
Mental stress can be detected in many ways and EEG is one of them. Regular mental stress …