Classification of pathological voice signals using self-similarity based wavelet packet feature extraction and Davies-bouldin criterion

The Analysis of Hand Movement Distinction Based on Relative Frequency Band Energy Method

For the purpose of successfully developing a prosthetic control system, many attempts have been made to improve the classification accuracy of surface electromyographic (SEMG) signals. Nevertheless, the effective feature extraction is still a paramount challenge for the classification of SEMG signals. The relative frequency band energy (RFBE) method based on wavelet packet decomposition was pro...

Fuzzy wavelet packet based feature extraction method applied to pathological voice signals classification

A New Algorithm for Voice Activity Detection Based on Wavelet Packets (RESEARCH NOTE)

Speech constitutes much of the communicated information; most other perceived audio signals do not carry nearly as much information. Indeed, much of the non-speech signals maybe classified as ‘noise’ in human communication. The process of separating conversational speech and noise is termed voice activity detection (VAD). This paper describes a new approach to VAD which is based on the Wavelet ...

Feature Extraction of Visual Evoked Potentials Using Wavelet Transform and Singular Value Decomposition

Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...

Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition

Background: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impac...