Analysis of Voice Pathology Evolution Using Entropy Rate

Scalassara, Paulo Rogério; Dájer, María Eugenia; Marrara, Jamille Lays; Maciel, Carlos Dias; Pereira, José Carlos

doi:10.1109/ism.2008.66

Cited by 11 publications

(5 citation statements)

References 23 publications

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“…The entropy approach has been widely used in the literature especially in biomedical engineering. New methods have been introduced to analyze and detect anomalous events such as epileptic seizure, coronary artery disease, and Alzheimer's disease from biomedical signals using different entropy types [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. The application of the entropy approach in mechanical engineering is given in [40][41][42][43][44][45].…”

Section: Introductionmentioning

confidence: 99%

Wavelet entropy and its application for flicker contribution evaluation

Silsüpür

Türkay

2018

IEEJ Transactions Elec Engng

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As a result of the integration of various new load types and generation units into electric power systems, power quality disturbances such as sag–swell, harmonics, inter‐harmonics, and flicker have come into focus in the last decades. Among these disturbances, flicker is one of the serious power quality issues for both power system operators and users. In addition to having direct effects on human life such as the discomfort caused by visual disturbance, flicker may cause incorrect operations of electrical devices. Furthermore, finding a dominant flicker source in order to mitigate it and supply high‐quality power to users are the main tasks of network operators. The measurement of the flicker level is defined in the IEC 61000‐4‐15 standard as measured by a flicker meter; however, it deals only with voltage signals and is not sufficient to understand the contribution of the load and background power systems separately. Therefore, this paper proposes new approaches to the evaluation of flicker characteristics using simulated and real signals. The novelty of this paper is that it investigates the flicker characteristics in the light of multi‐resolution wavelet analysis and information‐theory‐based wavelet energy entropy analysis together and proposes a new index to interpret flickers' responsibility in load and flicker source detection. The proposed method uses only voltage and current signals and does not require additional calculation of any network parameter such as the system impedance. The proposed method is validated by simulations as well as site measurements, and the results show the accuracy and suitability of the proposed method. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Section: Introductionmentioning

confidence: 99%

Wavelet entropy and its application for flicker contribution evaluation

Silsüpür

Türkay

2018

IEEJ Transactions Elec Engng

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“…The application of the rate of entropy can be found in many areas such as economics (Bentes, et al, 2008), medical sciences (Scalassara et al, 2008) statistical mechanics (Kirchnov, 2008), stochastic processes (Peres and Quas, 2011;Rached et al, 2004), statistics and related fields (Andai, 2009), (Jenssen and Eltoft, 2008) and biomedical engineering (Lake, 2006). This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

The Rate of Entropy for Gaussian Processes

Golshani¹

2015

JSRI

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Abstract.In this paper, we show that in order to obtain the Tsallis entropy rate for stochastic processes, we can use the limit of conditional entropy, as it was done for the case of Shannon and Renyi entropy rates. Using that we can obtain Tsallis entropy rate for stationary Gaussian processes. Finally, we derive the relation between Renyi, Shannon and Tsallis entropy rates for stationary Gaussian processes.

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“…Com isso, mostrou-se, de forma semelhante ao apresentado em Scalassara et al (2008a), que os sinais de nódulo apresentam valores maiores de entropia do que os sinais saudáveis, conforme apresentado na Figura 7.1. Esse estudo foi apresentado no Tenth IEEE International Symposium on Multimedia (Scalassara et al, 2008b).…”

Section: Contribuição Científicaunclassified

“…Figura 7.1: Diferenciação das curvas de convergência da entropia para alguns dos sinais de voz saudáveis e de nódulo, conforme apresentado em Scalassara et al (2008b).…”

Section: Contribuição Científicaunclassified

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Utilização de medidas de previsibilidade em sinais de voz para discriminação de patologias de laringe

Scalassara¹

Self Cite

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Eu gostaria de agradecer, inicialmente, a Deus, pela iluminação muito necessária no desenvolvimento deste trabalho. Também, por ter me capacitado a vencer a "inércia de não fazer nada" e a nunca desistir quando as coisas ficavam difíceis.Logo em seguida, um agradecimento muito especial a minha esposa Melissa, pois ela suportou todas as dificuldades junto comigo, dividindo o "peso do fardo" a ser carregado. Além disso, perdeu muitas horas da minha companhia quando tive que "por a mão na massa". Também, aos meus pais por sempre me incentivarem a continuar e a pensar no futuro. E, claro, por me ensinarem a estudar! Agradeço aos meus orientadores, profs. Pereira e Maciel, por me auxiliarem, discutirem os problemas, terem paciência e ajudarem no desenvolvimento deste trabalho. As conversas e conselhos foram imprescindíveis.Obrigado também às fonoaudiólogas Eugenia e Jamille por terem analisado tantas vozes quantas foram necessárias para os estudos e por terem me ajudado com a parte fisiológica "da coisa".Um agradecimento também ao pessoal do LPS e do LIM, por terem contribuído com discussões, materiais e muitas risadas.Agradeço, também, a todos que me ajudaram durante minha estada em Iowa City. Aos profs. Karnell e Titze por discutirem sobre análise de voz, a fonoaudióloga Abby por coletar diversos sinais e ao prof. Diego Moreira pelas discussões matemáticas, as quais ajudaram muito a ver os problemas por outra perspectiva.Por fim, um agradecimento especial à Fapesp por ter me financiado este tempo todo com duas bolsas, as quais foram essenciais para uma melhor qualidade de vida neste período. vii viii "É muito difícil fazer previsões, especialmente sobre o futuro."

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Analysis of Voice Pathology Evolution Using Entropy Rate

Cited by 11 publications

References 23 publications

Wavelet entropy and its application for flicker contribution evaluation

Wavelet entropy and its application for flicker contribution evaluation

The Rate of Entropy for Gaussian Processes

Utilização de medidas de previsibilidade em sinais de voz para discriminação de patologias de laringe

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