Efficient Noise Cancellation in Lung Signals Using Pipelined Adaptive LMS Algorithm

The proposed work focuses on the use of the Pipelined Adaptive LMS algorithm as an effective noise cancellation technique in lung signals. The LMS algorithm is an adaptive filtering technique that has the capability to remove noise from signals by adjusting filter coefficients based on the input data. The study employs MATLAB and ModelSim-Altera as software tools to implement the algorithm. The outcomes showcase the efficacy of the Pipelined Adaptive LMS algorithm for canceling noise in lung signals. This research provides valuable insights into the application of adaptive filtering methods in medical applications, highlighting the potential of these techniques to improve the quality of medical signal processing. Additionally, the study emphasizes the importance of optimizing algorithm performance to ensure successful Application in real-world scenarios is crucial. This study contributes to the advancement of sophisticated noise cancellation techniques for medical applications and underscores the significance of adapting these techniques to improve patient care.