The selection of an optimal segmentation region in physiological signals

• Tipo: Artigo em Revista Científica Internacional
• Data: 2023

Autores

Oliveira, J (Autor) Outra; Carvalho, M (Autor) Outra; Nogueira, D (Autor) Outra; Coimbra, M (Autor) FCUP

Revista

Título: International Transactions in Operational Research

Vol. 30

Páginas: 601-618

ISSN: 0969-6016

Editora: Wiley-Blackwell

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00W-AKS

DOI: 10.1111/itor.13138

Abstract (EN): Physiological signals are often corrupted by noisy sources. Usually, artificial intelligence algorithms analyze the whole signal, regardless of its varying quality. Instead, experienced cardiologists search for a high-quality signal segment, where more accurate conclusions can be draw. We propose a methodology that simultaneously selects the optimal processing region of a physiological signal and determines its decoding into a state sequence of physiologically meaningful events. Our approach comprises two phases. First, the training of a neural network that then enables the estimation of the state probability distribution of a signal sample. Second, the use of the neural network output within an integer program. The latter models the problem of finding a time window by maximizing a likelihood function defined by the user. Our method was tested and validated in two types of signals, the phonocardiogram and the electrocardiogram. In phonocardiogram and electrocardiogram segmentation tasks, the system's sensitivity increased on average from 95.1% to 97.5% and from 78.9% to 83.8%, respectively, when compared to standard approaches found in the literature.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 18