[图书][B] The illustrated wavelet transform handbook: introductory theory and applications in science, engineering, medicine and finance

PS Addison - 2017 - taylorfrancis.com
This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and
Applications in Science, Engineering, Medicine and Finance has been fully updated and …

Denoising of ECG signals using weighted stationary wavelet total variation

P Madan, V Singh, DP Singh, M Diwakar… - … Signal Processing and …, 2022 - Elsevier
ECG signals capture the electrical activity of the heart and can be used to determine its
health. The P-QRS-T morphological features of the ECG may be used to identify a variety of …

A new modified wavelet-based ECG denoising

Z Wang, J Zhu, T Yan, L Yang - Computer assisted surgery, 2019 - Taylor & Francis
Purpose: Wavelet denoising is one of the denoising methods commonly used for ECG
signals. However, due to the frequency overlap between the EMG and ECG, the feeble …

Automatic detection of epilepsy and seizure using multiclass sparse extreme learning machine classification

Y Wang, Z Li, L Feng, C Zheng… - … methods in medicine, 2017 - Wiley Online Library
An automatic detection system for distinguishing normal, ictal, and interictal
electroencephalogram (EEG) signals is of great help in clinical practice. This paper presents …

Hardware design of multiclass SVM classification for epilepsy and epileptic seizure detection

Y Wang, Z Li, L Feng, H Bai… - IET Circuits, Devices & …, 2018 - Wiley Online Library
An automatic detection system for distinguishing healthy, ictal, and inter‐ictal EEG signals
plays an important role in medical practice. This paper presents a very large scale …

Implementation of a non-linear SVM classification for seizure EEG signal analysis on FPGA

S Shanmugam, S Dharmar - Engineering Applications of Artificial …, 2024 - Elsevier
An automatic detection method for disease diagnosis plays an important role in the medical
field. A computer-aided diagnosis (CAD) system for seizure detection using …

Improved pipelined wavelet implementation for filtering ECG signals

A Milchevski, M Gusev - Pattern Recognition Letters, 2017 - Elsevier
We present a novel algorithm for digital filtering of an electrocardiogram (ECG) signal
received by both stationary and non-stationary sensors. The basic idea of digital ECG signal …

Noise reduction of ECG signals through genetic optimized wavelet threshold filtering

H He, Z Wang, Y Tan - 2015 IEEE International Conference on …, 2015 - ieeexplore.ieee.org
The Electrocardiogram (ECG) is a valuable signal recording the heart's electrical activity.
The filtering quality of ECG signals directly affects the medical diagnosis. Since wavelet …

VLSI design of multiclass classification using sparse extreme learning machine for epilepsy and seizure detection

Y Wang, Q Zhou, J Luo, Y Lu, H Wang… - IEICE Electronics …, 2022 - jstage.jst.go.jp
An automatic detection system for distinguishing healthy, ictal, and inter-ictal EEG signals is
of importance in clinical practice. This paper presents a low-complexity three-class …

Epileptic seizure classification using gradient tree boosting classifier

MA Tanveer, A Salman - Proceedings of the 2019 9th International …, 2019 - dl.acm.org
Analysis of electroencephalography (EEG) is widely used for the diagnosis of epilepsy in
which relevant information extraction from EEG signals poses great challenge due to noise …