Lung sound signal (LSS) measurements are taken to aid in the diagnosis of various diseases. Their interpretation is difficult however due to the presence of interference generated by the heart. In this paper, the adaptive line enhancer (ALE) is employed for reducing heart sound signal (HSS) from lung sound recordings. In this paper thirteen day new born baby girl’s lung sound signal is taken as an input to an adaptive line enhancer, and for updating the weights LMS algorithm has used. This performance is done by using MATLAB 7.0. More over linear predictive FIR filter is used for detecting the interference from the input signal. The architecture is validated in MATLAB, SNR and MSE are calculated. Verilog code is written and ALE has been successfully modeled and has been synthesized using Xilinx 9.1i, cadence and synopsis. The Area, power and timing reports are compared using these three tools. The ASIC design is carried on Synopsys tools.
">Lung sound signal (LSS) measurements are taken to aid in the diagnosis of various diseases. Their interpretation is difficult however due to the presence of interference generated by the heart. In this paper, the adaptive line enhancer (ALE) is employed for reducing heart sound signal (HSS) from lung sound recordings. In this paper thirteen day new born baby girl’s lung sound signal is taken as an input to an adaptive line enhancer, and for updating the weights LMS algorithm has used. This performance is done by using MATLAB 7.0. More over linear predictive FIR filter is used for detecting the interference from the input signal. The architecture is validated in MATLAB, SNR and MSE are calculated. Verilog code is written and ALE has been successfully modeled and has been synthesized using Xilinx 9.1i, cadence and synopsis. The Area, power and timing reports are compared using these three tools. The ASIC design is carried on Synopsys tools.