EGG signal classification using statistical analysis
نویسندگان
چکیده
The method is used to register the laryngeal behavior indirectly by measuring change in the electrical impedance across the throat during speech or voice. In this Electroglottography (EGG) signal acquisition, the electrodes are made of steel. They have the form of rectangles covering an area of 10.75 cm 2 . It is designed as a ring electrode encircling each of the two other electrodes. The electrodes are mounted on a flexible band whose length is adjusted to hold the electrodes in a steady position and to still allow the subject to comfortably speak and breathe naturally. The electrodes are mounted on a small holder which is pressed against the throat by hand. A signal generator supplies an AC sinusoidal current usually ranging from 2 MHz. The RF carrier signal is amplitude modulated by the modulating speech/voice signal and the demodulated signal is extracted. The variations in the signal correspond to the vocal fold abduction/laryngeal movement. For normal and pathology conditions, the results are recorded. These values form a feature vector, which reveals information regarding pathology. Principal component analysis technique (PCA) is used for classification, giving successful results for the specific data set considered.
منابع مشابه
A COMPARATIVE ANALYSIS OF WAVELET-BASED FEMG SIGNAL DENOISING WITH THRESHOLD FUNCTIONS AND FACIAL EXPRESSION CLASSIFICATION USING SVM AND LSSVM
This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...
متن کاملA Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns
Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work. Every fourth cycle of the instantaneous current signal, the mean is computed and carried into the next cycle to discover nonlinearities in the signal. A fault detection task is complete...
متن کاملSilent and voiced/unvoiced/mixed excitation (four-way) classification of speech
We present an algorithm for automatically classifying speech into four categories: silent and speech produced by three types of excitation, namely, voiced, unvoiced, and mixed (a combination of voiced and unvoiced). The algorithm uses two-channel (speech and electroglottogram) signal analysis and has been tested on data from six speakers (three male and three female), each speaking five sentenc...
متن کاملClassification of parasite egg cells using gray level cooccurence matrix and kNN
Parasite eggs are around 20 to 80 μm dimensions, and they can be seen under microscopes only and their detection requires visual analyses of microscopic images, which requires human expertise and long analysis time. Besides visual analysis is very error prone to human procedures. In order to automatize this process, a number of studies are proposed in the literature. But there is still a gap be...
متن کاملFault detection, classification and location methodology for solar microgrids using current injection, online phaselet transform, mathematical morphology filter and signal energy analysis
In this paper, a new method for detection and fault location and classification in MTDC solar microgrid is presented. Some issues such as expanding renewable energy sources and DC loads and efforts to increase power quality and reduce the environmental impact of electricity generation have led to the expansion of solar networks. Identifying the types and locations of faults is important to ensu...
متن کامل