Digital Stethoscope Research Paper

REVIEW OF A LOW COST DIGITAL STETHOSCOPE

B. Revanth Reddy1, P. Ramakrishna2, S. Roji Marjorie3
1,2,3Department of Electronics and Communication Engineering, Saveetha School of Engineering, Saveetha University, India.

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Acoustic stethoscopes have low sound levels. Digital stethoscope overcomes this issue by amplifying body sounds electronically. Acoustic stethoscope can be changed into a digital stethoscope by inserting an electric capacity microphone onto its head. As the sound signals are transmitted electronically, it can be wireless and can provide noise reduction. Wireless transmission of heartbeat rate can be done using IOT techniques. Heart sounds received from the microphone are processed,

Stethoscope in general has a function for auscultation, which is listening to the sounds that occur in the body. The sound produced by the biological activity of the body's organs, like the heart, lungs and digestive system. The heart is one organ that plays a role in the circulatory system. Contraction of the heart that can cause pulsation felt in the arteries in some places. Instrument used for the detection of clinically sound heart is an acoustic stethoscope. Acoustic stethoscope has a weakness, depending on the hearing of each physician. Diagnosis of each physician may vary. Sensitivity of the ear of each doctor is different. Noise signals generated in the electronic stethoscope will be analyzed using Wavelet. In this research, recognition of heart sounds using a stethoscope sound signal based on wavelet decomposition. Heart sound signal is decomposed up to level 8 using Daubechies3 wavelet (db3). Energy of each subband is calculated spectogram. Analysis of cardiac auscultation signals with wavelet daubachies, system can calculate the value of heartrate with 78% for heart sound pattern of early and late systolic murmur, 63% Diastolic heart sound patterns Rumble and 85% for normal heart sound

It presents a complete heart sound analysis system covering from the segmentation of beat cycles to the final determination of heart conditions. Skilled cardiologists probe heart sounds by electronic stethoscope through human ears, but interpretation of heart sounds is a very special skill which is quite difficult to teach in a structured way. Because of this reason, automatic heart sound analysis in computer systems would be very helpful for medical staff. The kernels of heart beat cycle segmentation and recognition are based on autocorrelation, short-time Fourier transform, and support vector machines. The experiments are done by a public heart sound database released by Texas Heart Institute. A very promising recognition rate has been