Physiological-signal-based emotion recognition: An odyssey from methodology to philosophy
W Li, Z Zhang, A Song - Measurement, 2021 - Elsevier
Exploration on emotions continues from past to present. Nowadays, with the rapid
advancement of intelligent technology, computer-aided emotion recognition using …
advancement of intelligent technology, computer-aided emotion recognition using …
EEG-based affective computing in virtual reality with a balancing of the computational efficiency and recognition accuracy
The field of VR-EEG affective computing is rapidly progressing. However, it faces challenges
such as lacking a solid psychological theory foundation, limited classification accuracy, and …
such as lacking a solid psychological theory foundation, limited classification accuracy, and …
Analysis of a Backpropagation Neural Network Training Algorithm for EEG-Based Drowsiness Identification
A Rahmawati, MAS Yudono… - … on Radar, Antenna …, 2023 - ieeexplore.ieee.org
Drowsiness, a major cause of car accidents, is detectable through EEG signal feature
classification. This study emphasizes machine learning for EEG signal analysis, focusing on …
classification. This study emphasizes machine learning for EEG signal analysis, focusing on …
Towards Improved Classification of Perceived Stress using Time Domain Features
Perceived stress is the predominant mental health concern in this age of development and
progress. Timely and precise recognition of perceived stress is vital for appropriate and …
progress. Timely and precise recognition of perceived stress is vital for appropriate and …
Exploring EEG Frequency Bands as a Feature for Machine Learning in Drowsiness Detection
A Darojatun, P Hidayatulloh… - … on Radar, Antenna …, 2023 - ieeexplore.ieee.org
Drowsiness can be detected by processing brainwaves that was recorded using
Electroencephalography (EEG). The EEG signals consist of delta, theta, alpha, beta and …
Electroencephalography (EEG). The EEG signals consist of delta, theta, alpha, beta and …