Nonlinear Dynamical Analysis of Normal Voices

Dájer, María Eugenia; Pereira, J.C.; Maciel, Carlos Dias

doi:10.1109/ism.2005.84

Cited by 13 publications

(15 citation statements)

References 28 publications

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“…In 2005, Dajer et al [45] performed a correlation analysis between NLD and AAV. For nonlinear analysis, the authors implemented the embedding delay using the mutual information method [46], while acoustic analysis was made by means of typical features such as Jitter, Shimmer, pitch amplitude and coefficient of excess (EX coefficient), which is defined as the relationship between the fourth statistical moment and the squared of the second statistical moment of the signal [47].…”

Section: Nonlinear Dynamics Analysis -Nldmentioning

confidence: 99%

Acoustic Analysis and Non Linear Dynamics Applied to Voice Pathology Detection: A Review

Orozco-Arroyave

Vargas-Bonilla²,

Delgado-Trejos³

2012

RPTSP

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A complete review of scientific studies and relevant patents oriented to voice pathology detection is presented in order to provide a good and quick reference for readers who want to understand how the field of automatic detection of voice disorders has evolved. Referenced works are divided into three groups, one focused on classical Acoustic Analysis of Voice (AAV), second on Non Linear Dynamics (NLD) and third on different and relevant patents presented in the development of systems for the automatic evaluation of pathological voices. The first group comprises not only typical acoustics but also noise measures and Cepstral analysis. In terms of NLD, both complexity measures and different versions of the entropies have been included, as well as other features. The patents referenced here have been presented from 2003 to 2011 in the patents offices located in United States, Europe and Asia.

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Section: Nonlinear Dynamics Analysis -Nldmentioning

confidence: 99%

Acoustic Analysis and Non Linear Dynamics Applied to Voice Pathology Detection: A Review

Orozco-Arroyave

Vargas-Bonilla²,

Delgado-Trejos³

2012

RPTSP

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“…These voice signals are part of a voice database of the Group of Bioengineering of the School of Engineering of São Carlos at the University of São Paulo, Brazil. These signals were collected along the past ten years and used in several studies (Rosa et al, 2000;Dajer et al, 2005).…”

Section: Voice Samplesmentioning

confidence: 99%

“…In order to describe the nonlinear dynamic characteristics of voice signals, sustained vowel data set was analyzed with ANL (Análise Não-Linear) software (Dajer et al, 2005). This piece of software was developed using Matlab 7.0 and the Tisean Package (Hegger et al, 1999;Kantz and Schreiber, 2004).…”

Section: Phase Space Reconstruction Techniquementioning

confidence: 99%

Voice Signals Characterization Through Entropy Measures

Scalassara¹,

Dájer²,

Maciel³

et al. 2008

Proceedings of the First International Conference on Bio-Inspired Systems and Signal Processing

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Human voice has been a matter of interest for different areas as technological development and medical sciences. In order to understand the dynamic complexity of healthy and pathologic voice, researchers have developed tools and methods for analysis. Recently nonlinear dynamics has shown the possibility to explore the dynamic nature of voice signals from a different point of view. The purpose of this paper is to apply entropy measures and phase space reconstruction technique to characterize healthy and nodule affected voices. Two groups of samples were used, one from healthy individuals and the other from people with nodule in the vocal fold. They are recordings of sustained vowel /a/ from Brazilian Portuguese. The paper shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Since the nodule pathology is characterized by an increase in the signal's complexity and unpredictability, measures of entropy are well suited due to its sensibility to uncertainty. The results showed that the nodule group had a higher entropy values. This suggests that these techniques may improve and complement the recent voice analysis methods available for clinicians.

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“…Uma dessas técnicas é a análise dos Padrões Visuais de Dinâmica Vocal (PVDV) que permite a visualização da complexidade dinâmica do sinal de voz. Com esta técnica a vibração das pregas vocais pode ser mostrada como trajetórias num espaço de fase reconstruído evidenciando a dinâmica do sistema (DAJER;MACIEL, 2005).…”

Section: -Introduçãounclassified

Padrão visual da dinâmica vocal como instrumento para o diagnóstico da disfagia em pacientes com alterações neurológicas

Marrara¹

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Nonlinear Dynamical Analysis of Normal Voices

Cited by 13 publications

References 28 publications

Acoustic Analysis and Non Linear Dynamics Applied to Voice Pathology Detection: A Review

Acoustic Analysis and Non Linear Dynamics Applied to Voice Pathology Detection: A Review

Voice Signals Characterization Through Entropy Measures

Padrão visual da dinâmica vocal como instrumento para o diagnóstico da disfagia em pacientes com alterações neurológicas

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