most citedUnsupervised detection and classification of heartbeats using the dissimilarity matrix in PCG signals

21 citations · 64 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS202420 cited

Classification of Adventitious Sounds Combining Cochleogram and Vision Transformers

Loredana Daria Mang, Francisco David Gonzalez Martinez, Damian Martinez Munoz +2

Early identification of respiratory irregularities is critical for improving lung health and reducing global mortality rates. The analysis of respiratory sounds plays a significant…

eess.AS20247 cited

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

Antonio J. Muñoz-Montoro, Pablo Revuelta-Sanz, Damian Martínez-Muñoz +2

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 pr…

eess.AS202421 cited

Unsupervised detection and classification of heartbeats using the dissimilarity matrix in PCG signals

J. Torre-Cruz, D. Martinez-Munoz, N. Ruiz-Reyes +3

The proposed system consists of a two-stage cascade. The first stage performs a rough heartbeat detection while the second stage refines the previous one, improving the temporal lo…

eess.AS20244 cited

An incremental algorithm based on multichannel non-negative matrix partial co-factorization for ambient denoising in auscultation

Juan De La Torre Cruz, Francisco Jesus Canadas Quesada, Damian Martinez-Munoz +3

The aim of this study is to implement a method to remove ambient noise in biomedical sounds captured in auscultation. We propose an incremental approach based on multichannel non-n…

cs.SD202412 cited

Improving snore detection under limited dataset through harmonic/percussive source separation and convolutional neural networks

F. D. Gonzalez-Martinez, J. J. Carabias-Orti, F. J. Canadas-Quesada +3

Snoring, an acoustic biomarker commonly observed in individuals with Obstructive Sleep Apnoea Syndrome (OSAS), holds significant potential for diagnosing and monitoring this recogn…