AIMC Topic: Wavelet Analysis

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A Feature Fusion Model Based on Temporal Convolutional Network for Automatic Sleep Staging Using Single-Channel EEG.

IEEE journal of biomedical and health informatics
Sleep staging is a crucial task in sleep monitoring and diagnosis, but clinical sleep staging is both time-consuming and subjective. In this study, we proposed a novel deep learning algorithm named feature fusion temporal convolutional network (FFTCN...

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...

A hybrid model for the classification of Autism Spectrum Disorder using Mu rhythm in EEG.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Autism Spectrum Disorder (ASD) is a condition with social interaction, communication, and behavioral difficulties. Diagnostic methods mostly rely on subjective evaluations and can lack objectivity. In this research Machine learning (ML) a...

Deep learning approach for skin melanoma and benign classification using empirical wavelet decomposition.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Melanoma is a malignant skin cancer that causes high mortality. Early detection of melanoma can save patients' lives. The features of the skin lesion images can be extracted using computer techniques to differentiate early between melanom...

Research on breast cancer pathological image classification method based on wavelet transform and YOLOv8.

Journal of X-ray science and technology
 Breast cancer is one of the cancers with high morbidity and mortality in the world, which is a serious threat to the health of women. With the development of deep learning, the recognition about computer-aided diagnosis technology is getting higher ...

Feature Learning Networks for Floor Sensor-based Gait Recognition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep learning (DL) has become a powerful tool in many image classification applications but often requires large training sets to achieve high accuracy. For applications where the available data are limited, this can become a severely limiting factor...

2D Wavelet-Scalogram Deep-Learning for Seizures Pattern Identification in the Post-Hypoxic-Ischemic EEG of Preterm Fetal Sheep.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Neonatal seizures after an hypoxic-ischemic (HI) event in preterm newborns can contribute to neural injury and cause impaired brain development. Preterm neonatal seizures are often not detected or their occurrence underestimated. Therefore, there is ...

The Effectiveness of Narrowing the Window size for LD & HD EMG Channels based on Novel Deep Learning Wavelet Scattering Transform Feature Extraction Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The use of the Electromyogram (EMG) signals as a source of control to command externally powered prostheses is often challenged by the signal complexity and non-stationary behavior. Mainly, two factors affect classification accuracy: selecting the op...