Trends in Phonocardiogram Signal processing
Trends in Phonocardiogram Signal processing
The most important organ in a human body is a heart that uses a pump like a mechanism to supply blood to all areas of the body. Electrical and mechanical activities are performed during the pumping action which results in blood flow. For the normal day to day life activities of the human body, the healthy heart is very important because blood transports significant nutrients into the body part. Heart-related illnesses, called cardiovascular illnesses (disease) (CVD), are answerable for a significant amount of deaths worldwide. According to the World Health Organization (WHO) reports, the effect of CVDs is 33 percent of all deaths. Different modalities to monitor heart health are proposed. Electrocardiogram or ECG is the most common among these. ECG signal consists of P Q R S and T patterns per cardiac cycle. The duration of a healthy human heart is 0.8 seconds. Further, the cardiac cycle is divided into systole and diastole period which are associated with the shrinkage and relaxation of the heart muscles. Majority of the time the heart is in the diastolic period.
A PCG (phonocardiogram) is a method of analyzing heart sounds, which can be visually represented on a chart. The PCG is the functional condition of the heart of the form bio-acoustic statistics nature. The detection of cardiac diseases, the effect of certain cardiac drugs on the condition of the heart are analysed to determine the abnormalities using PCG signal in a non-invasive method.
There are two main sounds in a typical cardiac cycle which are Ist heart (S1) and 2 nd heart (S2) tone. S1 arises at the onset of ventricular contractions in the ECG signal which corresponds to the QRS complex. S1 heart sound associated with four components which are discussed as follows, the first component corresponding to the closing of AV valves (mitral and Tricuspid valves). The second Component is associated with decelerating blood flow by the sudden stress of the closed AV valves. This part also involves opening semi-lunar valves and withdrawing blood from ventricles. The Third Factor is caused by blood oscillation between the aorta root and the walls of the ventricle. The fourth aspect is due to vibrations in the expelled blood caused by friction flowing quickly through the uphill aorta and lung artery.
S2 triggered by semi-lunar valve closings. S2 has two components and the Istcomponent is because of the aortic valve end (A2), and the 2nd is because of the pulmonary valve closure (P2). A2 arrives a few milliseconds early before P2.
The third heart sound (S3), is the sudden termination of the rapid filling phase of the ventricle. During this phase of the diastole cycle, the ventricles are filled with blood and their walls relax. S3 is defined as a low-frequency nature waveform.
S4 is triggered by the atrial contractions that displace the blood into the ventricles, and the sound predominates in children.
Table 1. PCG Sound Frequency and Time duration
Sl.no | PCG Sound Component | Frequency (Hz) | Time Duration in milli seconds |
1 | S1 | 30-150 | 50-100 |
2 | S2 | 225-400 | 25-50 |
3 | S3 | 10-100 | 40-80 |
4 | S4 | 10-50 | 30-60 |
As observed from table 1 that S1 and S2 components are easily observed in the PCG than the S3, and S4 components. Here we can find the time element from S1 to S2 is well-known as systole, and the time span from S2 to S1 is identified as cardiac cycle diastole.
PCG provides more information than ECG for monitoring the status of the cardiac valves. Measuring the heart rate variability (HRV) based on a recording of heart sounds (phonocardiogram) is used for monitoring the autonomic nervous system. The changes in HRV are derived from a heart’s sound signals, which are readily highly collectible with a microphone or listening instrument used in auscultation and are readily accessible to patients, providing fast diagnosis and Information transfer.
Heart sounds and hums are of fairly small frequency and are bounded to around 10–1000 Hz in the unit. Cardiac murmurs are classified into two categories like stenosis ( not closing) and insufficiency (not opening).
A. Early method of acoustic signal acquisition:
Acoustic stethoscopes mechanically transmit sound from a chest part to the hearer ‘s ears through air-filled hollow tubes. The diaphragm and the bell function as two filters that transmit higher frequency sounds and lower frequency sounds respectively. Electronic stethoscopes work in a similar manner, but the sound is converted to an electronic signal that is transmitted by wire to the listener. Functionalities sometimes used in electronic stethoscopes are signal amplification, filters imitating the diaphragm and bell functions, and, in some cases, recording capabilities to enable data storage.
B.PCG signal processing methods
Since PCG signals are associated with multiple components and low SNR valve make it difficult to process the signal through filtering methods. PCG signal is also a dynamic and non-stationary signal. Therefore The PCG signal is first converted into a WSS process over a window of observation and then the signal processing is applied. Recently EMD method is a very promising one than the wavelet decomposition of PCG signals. CWT, STFT, and HHT are some of the popular signal processing methods associated with PCG.
By nature of occurrence S1 and S2 sounds are tracked without much difficult through Hilbert transform-based envelope detection. However, the individual components are not much visible in this method. Therefore a mathematical sparse based segregation technique is quite useful in these cases. S3 and S4 sounds are produced by means of nonlinear signal decomposition and localization methods for the time duration. The Hilbert Vibration Decomposition (HVD) method is used in this technique to convert the signal into multiple subcomponents while preserving the phase values. Further, the decomposed signal components are processed through the time-Frequency localization which is different from Wavelet transforms. A combination of HVD with bio-inspired algorithms such as PSO, GA_PSO, Firefly, and Elephant herd optimization is quite useful in locating S3 and S4 signals for detect.