The system is a point-of-care (POC) device that can deliver heart-care services to the rural population and bridge the rural–urban divide in healthcare delivery.Normal heart sounds provide an indication of the general state of the heart in terms of rhythm and contractility, while changing its signature due to any cardiovascular pathology for additional murmurs that contributesignificant information in diagnosis. Eventually, the presence of lung sound affects the signature characteristics of heart sound when mixed with the later one in spatio-temporal domain, further separation of which becomes difficult through normal filtering approaches. This work aims todetermine a framework for utilization of automated HS analysissystem for community healthcare and healthcare inclusion. It focuses on the development of a standalone system using a TI-MSP430, aiming to acquire and filter the heart sound signal based on modern signal processing algorithms.Initially, the acquired sound waves are passed through a band pass filter bank followed by an amplification unit, enabling elimination of high frequency noise signals and subsequent amplification of the signal of interest. When captured at MSP430 terminal, the microcontroller converts the analog signal into its digital counterpart, maintaining Nyquist rate and stores the time-sequence data into its on-board memory blocks. The computational algorithm, based on adaptive and wavelet signal processing techniques, integrated on the hardware platform further process the acquired data to reduce the effect of lung sound from the composite signal through various statistical measures. Output of the MSP430 system can be either fed to a digital display or microphone system for accurate determination of the heart sounds which can provide diagnostic clinical inference about the heart in health and pathology.