AIMC Topic: Wavelet Analysis

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Mental Stress Detection Using a Wearable In-Ear Plethysmography.

Biosensors
This study presents an ear-mounted photoplethysmography (PPG) system that is designed to detect mental stress. Mental stress is a prevalent condition that can negatively impact an individual's health and well-being. Early detection and treatment of m...

Analysis of the Cardiorespiratory Pattern of Patients Undergoing Weaning Using Artificial Intelligence.

International journal of environmental research and public health
The optimal extubating moment is still a challenge in clinical practice. Respiratory pattern variability analysis in patients assisted through mechanical ventilation to identify this optimal moment could contribute to this process. This work proposes...

A Novel Pipeline Corrosion Monitoring Method Based on Piezoelectric Active Sensing and CNN.

Sensors (Basel, Switzerland)
In this study, a piezoelectric active sensing-based time reversal method was investigated for monitoring pipeline internal corrosion. An effective method that combines wavelet packet energy with a Convolutional Neural Network (CNN) was proposed to id...

Lung Sound Recognition Method Based on Wavelet Feature Enhancement and Time-Frequency Synchronous Modeling.

IEEE journal of biomedical and health informatics
Lung diseases are serious threats to human health and life, therefore, an accurate diagnosis of lung diseases is significant. The use of artificial intelligence to analyze lung sounds can aid in diagnosing lung diseases. Most of the existing lung sou...

Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Autism spectrum disorder (ASD), a neurodevelopment disorder, is characterized by significant difficulties in social interaction and emerges as a major threat to children. Its computer-aided diagnosis used by neurologists improves the detection proces...

An Efficient AP-ANN-Based Multimethod Fusion Model to Detect Stress through EEG Signal Analysis.

Computational intelligence and neuroscience
Stress is a universal emotion that every human experiences daily. Psychologists say stress may lead to heart attack, depression, hypertension, strokes, or even sudden death. Many technical explorations like stress detection through facial expression,...

Hybrid fuzzy inference rules of descent method and wavelet function for volatility forecasting.

PloS one
This research employs the gradient descent learning (FIR.DM) approach as a learning process in a nonlinear spectral model of maximum overlapping discrete wavelet transform (MODWT) to improve volatility prediction of daily stock market prices using Sa...

A Novel Computer-Vision Approach Assisted by 2D-Wavelet Transform and Locality Sensitive Discriminant Analysis for Concrete Crack Detection.

Sensors (Basel, Switzerland)
This study proposes FastCrackNet, a computationally efficient crack-detection approach. Instead of a computationally costly convolutional neural network (CNN), this technique uses an effective, fully connected network, which is coupled with a 2D-wave...

Classification Framework of the Bearing Faults of an Induction Motor Using Wavelet Scattering Transform-Based Features.

Sensors (Basel, Switzerland)
In the machine learning and data science pipelines, feature extraction is considered the most crucial component according to researchers, where generating a discriminative feature matrix is the utmost challenging task to achieve high classification a...

Wavelet LSTM for Fault Forecasting in Electrical Power Grids.

Sensors (Basel, Switzerland)
An electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way. Failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this rea...