An ambient denoising method based on multi‑channel non‑negative matrix factorization for wheezing detection

In this paper, a parallel computing method is proposed to perform the background denoising and wheezing detection from a multi-channel recording captured during the auscultation process. The proposed system is based on a non-negative matrix factorization (NMF) approach and a detection strategy. More...

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Detalles Bibliográficos
Autores: Muñoz Montoro, Antonio Jesús, Revuelta Sanz, Pablo, Martínez Muñoz, Damián, De La Torre Cruz, Juan, Ranilla, José
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2022
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/3336
Acceso en línea:https://doi.org/10.1007/s11227-022-04706-x
https://link.springer.com/article/10.1007/s11227-022-04706-x
https://hdl.handle.net/10953/3336
Access Level:acceso abierto
Palabra clave:Non-negative matrix factorization (NMF)
Singular value decomposition (SVD)
Parallel computing
Wheezing detection
Denoising
Multi-channel
Descripción
Sumario:In this paper, a parallel computing method is proposed to perform the background denoising and wheezing detection from a multi-channel recording captured during the auscultation process. The proposed system is based on a non-negative matrix factorization (NMF) approach and a detection strategy. Moreover, the initialization of the proposed model is based on singular value decomposition to avoid dependence on the initial values of the NMF parameters. Additionally, novel update rules to simultaneously address the multichannel denoising while preserving an orthogonal constraint to maximize source separation have been designed. The proposed system has been evaluated for the task of wheezing detection showing a significant improvement over state-of-the-art algorithms when noisy sound sources are present. Moreover, parallel and high-performance techniques have been used to speedup the execution of the proposed system, showing that it is possible to achieve fast execution times, which enables its implementation in real-world scenarios.