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Wavelet Analysis

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Real-time Classification of Diverse Reaching Motions Using RMS and Discrete Wavelet Transform Energy Values from EMG Signals for Human Assistive Robots.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
With advancing technology, human assistive robots have been developed to enhance daily efficiency for users. Focusing on the reaching motions of the upper limb, this study aims to propose a motion classification method based on electromyographic (EMG...

Transformer-Based Wavelet-Scalogram Deep Learning for Improved Seizure Pattern Recognition in Post-Hypoxic-Ischemic Fetal Sheep EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Hypoxic-ischemic (HI) events in newborns can trigger seizures, which are highly associated with later neurodevelopmental impairment. The precise detection of these seizures is a complex task requiring considerable very specialized expertise, undersco...

An arrhythmia classification using a deep learning and optimisation-based methodology.

Journal of medical engineering & technology
The work proposes a methodology for five different classes of ECG signals. The methodology utilises moving average filter and discrete wavelet transformation for the remove of baseline wandering and powerline interference. The preprocessed signals ar...

A novel ECG-based approach for classifying psychiatric disorders: Leveraging wavelet scattering networks.

Medical engineering & physics
Individuals with neuropsychiatric disorders experience both physical and mental difficulties, hindering their ability to live healthy lives and participate in daily activities. It is challenging to diagnose these disorders due to a lack of reliable d...

An integrated approach for advanced vehicle classification.

PloS one
This study is dedicated to addressing the trade-off between receptive field size and computational efficiency in low-level vision. Conventional neural networks (CNNs) usually expand the receptive field by adding layers or inflation filtering, which o...

Adaptive wavelet base selection for deep learning-based ECG diagnosis: A reinforcement learning approach.

PloS one
Electrocardiogram (ECG) signals are crucial in diagnosing cardiovascular diseases (CVDs). While wavelet-based feature extraction has demonstrated effectiveness in deep learning (DL)-based ECG diagnosis, selecting the optimal wavelet base poses a sign...

Optimizing functional brain network analysis by incorporating nonlinear factors and frequency band selection with machine learning models.

Medicine
The accurate assessment of the brain's functional network is seen as crucial for the understanding of complex relationships between different brain regions. Hidden information within different frequency bands, which is often overlooked by traditional...

MIMI-ONET: Multi-Modal image augmentation via Butterfly Optimized neural network for Huntington DiseaseDetection.

Brain research
Huntington's disease (HD) is a chronic neurodegenerative ailment that affects cognitive decline, motor impairment, and psychiatric symptoms. However, the existing HD detection methods are struggle with limited annotated datasets that restricts their ...

HFFTrack: Transformer tracking via hybrid frequency features.

Neural networks : the official journal of the International Neural Network Society
Numerous Transformer-based trackers have emerged due to the powerful global modeling capabilities of the Transformer. Nevertheless, the Transformer is a low-pass filter with insufficient capacity to extract high-frequency features of the target and t...

Enhanced EEG-based cognitive workload detection using RADWT and machine learning.

Neuroscience
Understanding cognitive workload improves learning performance and provides insights into human cognitive processes. Estimating cognitive workload finds practical applications in adaptive learning systems, brain-computer interfaces, and cognitive mon...