Noise pattern definition methodology for noise cancellation in coughs signals using an adaptive filter
Authors: Santiago Felipe Luna Romero, Christian Salamea Palacios
Abstract: Cough is the body’s defense mechanism to respond to foreign materials that are accidentally inhaled or caused internally by infections to clean the respiratory system. The cough also contains essential information about the airways of the lungs that helps in the diagnosis of diseases related to the lungs. The cough information contains important information as it is responsible for various respiratory diseases such as bronchitis, asthma, pneumonia, etc. Within the study of cough as an audio signal, different acquisition techniques have been created for its analysis. In these audios, there is the possibility of acoustic contamination of cough signals, interferences such as environmental ones, noise when a cough is registered. The sound of teeth, saliva when a person opens and closes their mouth, etc. Acoustic systems for noise cancellation and audio signal enhancement have become a major area of concern in the scientific community because noise drastically reduces the sound quality of cough signals, in addition, that, from a medical point of view, acoustic noise cancellation is vital, as a contaminated cough signal can lead to misdiagnosis by healthcare professionals. Therefore, it is necessary to filter out these noisy signals for proper and accurate analysis of cough signals. In this field, different filtering and noise cancellation techniques have been developed to obtain the cleanest possible cough audio signal. Within the scientific community, but it has been detected that these techniques present a generalization problem because they are configured to eliminate a single type of noise and the same acquisition environment. Therefore, this work proposes a methodology to create a reference signal (noise pattern) that can be used in adaptive filtering to minimize the noise produced in a cough record. This noise pattern is can incorporate information of all types of noises that contaminate a record cough signal. This reference signal has been created using a dataset of cough audio signals. The signal-to-noise ratio (SNR) has been used as the evaluation metric of the filtering quality. A system able to minimize the noise across all the record cough files using this methodology with an adaptive filtering technique has been created obtaining results closely to 0db, demonstrating the efficiency and generalization of the proposed technique that is part of the preprocessing phase in a system of characterization and classification of cough records.
Keywords: Snr, Adaptive Filter, Cough, Signal Processing, Perturbation Noise.
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