Key result
An Adaptive Line Enhancer with Least Mean Square algorithm was applied to separate heart sound signals from lung sound signals, evaluating error rate, signal-to-noise ratio, and execution time.
An Adaptive Line Enhancer with LMS algorithm can be used to separate heart sounds from lung sounds in real-time recordings, potentially improving lung sound analysis.
May support real-time cardiopulmonary signal separation; clinical validation needed before adoption.
This study presents a technique for separation of Heart Sound Signal (HSS) from Lung Sound Signal (LSS) using Adaptive Line Enhancer (ALE) with Least Mean Square (LMS) algorithm with real time recorded sound signal. While recording lung sounds, an incessant noise source takes place owing to heart sounds. This noise source severely contaminates the breath sound signal and interferes in the analysis of lung sounds. The proposed system is applied with different filter order and the results show the error rate of the Desired Sound Signal (DSS), Signal to Noise Ratio (SNR) and execution time.
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Sathesh et al. (2015) studied Heart and lung sound signal separation. Adaptive Line Enhancer (ALE) with Least Mean Square (LMS) algorithm was evaluated on Error rate of the Desired Sound Signal (DSS), Signal to Noise Ratio (SNR) and execution time. An Adaptive Line Enhancer with Least Mean Square algorithm was applied to separate heart sound signals from lung sound signals, evaluating error rate, signal-to-noise ratio, and execution time.
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