scholarly journals Wavelet-based statistical signal processing using hidden Markov models

1998 ◽  
Vol 46 (4) ◽  
pp. 886-902 ◽  
Author(s):  
M.S. Crouse ◽  
R.D. Nowak ◽  
R.G. Baraniuk
Keyword(s):  
Signal Processing ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Statistical Signal Processing

Speech Disorders Recognition using Speech Analysis

2013 ◽  
pp. 494-507 ◽  
Author(s):  
Khaled Necibi ◽  
Halima Bahi ◽  
Toufik Sari
Keyword(s):  
Signal Processing ◽  
Hidden Markov Models ◽  
Automatic Speech Recognition ◽  
Markov Models ◽  
Hidden Markov ◽  
Speech Disorders ◽  
Speech Analysis ◽  
Physical Problems ◽  
Processing Techniques ◽  
Signal Processing Techniques

Speech disorders are human disabilities widely present in young population but also adults may suffer from such disorders after some physical problems. In this context, the detection and further the correction of such disabilities may be handled by Automatic Speech Recognition (ASR) technology. The first works on the speech disorders detection began early in the 70s and seem to follow the same evolution as those on the ASR. Indeed, these early works were more based on the signal processing techniques. Progressively, systems dealing with speech disorders incorporate more ideas from ASR technology. Particularly, Hidden Markov Models, the state-of-the-art approaches in ASR systems, are used. This chapter reviews systems that use ASR techniques to evaluate pronunciation of people who suffer from speech or voice impairments. The authors investigate the existing systems and present the main innovation and some of the available resources.

scholarly journals Diagnosis of Left Ventricular Hypertrophy Based on Electrocardiogram Signal and Fuzzy Logic

2019 ◽  
Vol 35 (2) ◽  
Author(s):  
Tran Nhu Chi ◽  
Nguyen Thi Thanh Van ◽  
Le Van Chieu
Keyword(s):  
Signal Processing ◽  
Fuzzy Logic ◽  
Left Ventricular Hypertrophy ◽  
Hidden Markov Models ◽  
Ventricular Hypertrophy ◽  
Markov Models ◽  
Hidden Markov ◽  
Publishing House ◽  
Left Ventricular ◽  
Ecg Signal

Sokolow – Lyon index in detection of left ventricular hypertrophy is a hard limited index, so the clinical manifestation of the disease can be ignored when the measured index is near the threshold. Several proposed studies incorporate multiple index to improve diagnostic quality. However, the process of examination and diagnosis will be longer due to the need to collect more data. To solve this problem, the paper proposes a method of classifying left ventricular hypertrophy using fuzzy logic combining with digital signal processing techniques. The proposed method mainly uses the Sokolov-Lyon index (SV1+RV5/V6 ≥ 35 mm) for major changes in ECG signal but with four soft thresholds corresponding to the different clinical manifestations of the disease. In addition, a program is written in C++ language with QT Creator compiler also is developed to implement the algorithm. From there, the doctors can refer and propose to the patient's treatment regimen. Keywords ECG, left ventricular hypertrophy, signal processing, fuzzy logic. References [1] Malcolm S. Thaler, The only EKG book, seventh ed. Lippincott Williams & Wilinks, Philadelphia, 2012. [2] Vakili BA, Okin PM, Devereux RB, Prognostic implications of left ventricular hypertrophy, Am Heart J, 141(3) (2001) 334-341.https://doi.org/10.1067/mhj.2001.113218.[3] Tran Do Trinh, Tran Van Dong, How to read EGC signal, Medical Publishing House, 2011 (in Vietnamese).[4] Himanshu Gothwal1, Silky Kedawat1, Rajesh Kumar, Cardiac arrhythmias detection in an ECG beat signal using fast fourier transform and artificial neural network, J. Biomedical Science and Engineering 4 (2011) 289-296.https://doi.org/10.4236/jbise.2011.44039.[5] El-Sayed A. El-Dahshan, Genetic algorithm and wavelet hybrid scheme for ECG signal denoising, Journal of Telecommunications Systems 46(3) (2011) 209-215.https://doi.org/10.1007/s11235-010-9286-2.[6] C. Li, C. Zheng, and C. Tai, Detection of ECG characteristic points using wavelet transforms, IEEE Trans.Biomed. Eng 42(1) (1995) 21-28.https://doi.org/10.1109/10.362922.[7] A.K.M. Fazlul Haque1, Md. Hanif Ali1, M. Adnan Kiber2 and Md. Tanvir Hasan, Detection of small variations of ECG features using Wavelet, ARPN Journal of Engineering and Applied Sciences 4(6) (2009) 27-30.[8] Krimi Samar, Ouni Kas, Noureddine Ellouze, Using Hidden Markov Models for ECG Characterisation, Hidden Markov Models, Theory and Applications, 4 (2011) 151-165.https://doi.org/10.5772/13916.[9] Van Ngoc Tuyet, Bang Ai Vien, Nguyen Van Tri, Medical Journal Ho Chi Minh city, Diagnosis of left ventricular hypertrophy by ECG I 15(1) (2011) 135-140 (in Vietnamese).[10] Buckley, James J., Eslami, Esfandiar, Introduction to Fuzzy Logic and Fuzzy Sets, Physica-Verlag Heidelberg, Berlin, 2002. [11] Phan Xuan Minh, Nguyen Doan Phuoc, Fuzzy Control Theory, Science and Technics Publishing House, Ha Noi, 2006 (in Vietnamese).  

Sign in / Sign up

Export Citation Format

Share Document