Classification of PCG Signals: A Survey
نویسندگان
چکیده
Heart sounds are multi component non-stationary signals characterized as the normal phonocardiogram (PCG) signals and the pathological PCG signals. PCG is a weak biological signal mixed with strong background noise susceptible to interference from noise. The noise may be added due to various sources. The PCG signal has specific individual characteristics which are considered as a physiological sign in a biometric system. Literatures suggest that the
منابع مشابه
Automatic classification of normal and abnormal cardiac sounds by combining features based on wavelet transform and capstral coefficients extracted from PCG signals (Research Article)
Cardiac sounds are produced by the mechanical activities of the heart and provide useful information about the function of the heart valves. Due to the transient and unstable nature of the heart's sound and the limitation of the human hearing system, it is difficult to categorize heart sound signals based on what is heard from a stethoscope. Therefore, providing an automated algorithm for prima...
متن کاملPathologies cardiac discrimination using the Fast Fourir Transform (FFT) The short time Fourier transforms (STFT) and the Wigner distribution (WD)
This paper is concerned with a synthesis study of the fast Fourier transform (FFT), the short time Fourier transform (STFT and the Wigner distribution (WD) in analysing the phonocardiogram signal (PCG) or heart cardiac sounds. The FFT (Fast Fourier Transform) can provide a basic understanding of the frequency contents of the heart sounds. The STFT is obtained by calculating the Fourier tran...
متن کاملClassification of ECG signals using Hermite functions and MLP neural networks
Classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. This paper proposes a three module system for classification of electrocardiogram (ECG) beats. These modules are: denoising module, feature extraction module and a classification module. In the first module the stationary wavelet transform (SWF) is used for noise reduction of ...
متن کاملDetection and Classification of Emotions Using Physiological Signals and Pattern Recognition Methods
Introduction: Emotions play an important role in health, communication, and interaction between humans. The ability to recognize the emotional status of people is an important indicator of health and natural relationships. In DEAP database, electroencephalogram (EEG) signals as well as environmental physiological signals related to 32 volunteers are registered. The participants in each video we...
متن کاملDetection and Classification of Emotions Using Physiological Signals and Pattern Recognition Methods
Introduction: Emotions play an important role in health, communication, and interaction between humans. The ability to recognize the emotional status of people is an important indicator of health and natural relationships. In DEAP database, electroencephalogram (EEG) signals as well as environmental physiological signals related to 32 volunteers are registered. The participants in each video we...
متن کامل