EEG-Based Emotion Recognition Using Different Neural Network and Pattern Recognition Techniques A Review

2019 ◽  
Vol 7 (1) ◽  
pp. 615-618
Author(s):  
Y. M. Rajput ◽  
S. Abdul Hannan ◽  
M. Eid Alzahrani ◽  
Ramesh R. Manza ◽  
Dnyaneshwari D. Patil
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Emotion Recognition ◽  
Pattern Recognition Techniques

scholarly journals Cognitive Ergonomics Evaluation Assisted by an Intelligent Emotion Recognition Technique

2020 ◽  
Vol 10 (5) ◽  
pp. 1736
Author(s):  
Adrian Rodriguez Aguiñaga ◽  
Arturo Realyvásquez-Vargas ◽  
Miguel Ángel López R. ◽  
Angeles Quezada
Keyword(s):  
Pattern Recognition ◽  
Emotion Recognition ◽  
Facial Expressions ◽  
Situation Awareness ◽  
Well Being ◽  
Cognitive Effects ◽  
Work Activities ◽  
Pattern Recognition Techniques ◽  
Cognitive Ergonomics ◽  
Recognition Technique

The study of the cognitive effects caused by work activities are vital to ensure the well-being of a worker, and this work presents a strategy to analyze these effects while they are carrying out their activities. Our proposal is based on the implementation of pattern recognition techniques to identify emotions in facial expressions and correlate them to a proposed situation awareness model that measures the levels of comfort and mental stability of a worker and proposes corrective actions. We present the experimental results that could not be collected through traditional techniques since we carry out a continuous and uninterrupted assessment of the cognitive situation of a worker.

scholarly journals APPLICATION OF PATTERN RECOGNITION TECHNIQUES FOR FAULT DETECTION OF CLUTCH RETAINER OF TRACTOR

2018 ◽  
Vol 47 (1) ◽  
pp. 31-36
Author(s):  
Mostafa Bahrami ◽  
Hossein Javadikia ◽  
Ebrahim Ebrahimi
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Pattern Recognition ◽  
Fourier Transform ◽  
Artificial Neural Networks ◽  
Accurate Diagnosis ◽  
Pattern Recognition Techniques ◽  
The Neural Network ◽  
Power Spectral ◽  
Proposed Model

This study develops a technique based on pattern recognition for fault diagnosis of clutch retainer mechanism of MF285 tractor using the neural network. In this technique, time features and frequency domain features consist of Fast Fourier Transform (FFT) phase angle and Power Spectral Density (PSD) proposes to improve diagnosis ability. Three different cases, such as: normal condition, bearing wears and shaft wears were applied for signal processing. The data divides in two parts; in part one 70% data are dataset1 and in part two 30% for dataset2.At first, the artificial neural networks (ANN) are trained by 60% dataset1 and validated by 20% dataset1 and tested by 20% dataset1. Then, to more test of the proposed model, the network using the datasets2 are simulated. The results indicate effective ability in accurate diagnosis of various clutch retainer mechanism of MF285 tractor faults using pattern recognition networks.

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