Usefulness of Acoustic Studies on the Differential Diagnostics of Organic and Functional Dysphonia

Pruszewicz, A; Obrebowski, A; Swidziński, P; Demenko, Grażyna; Wika, Teresa; Wojciechowska, Anna

doi:10.3109/00016489109137412

Cited by 9 publications

(4 citation statements)

References 6 publications

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“…This is apparent in the concept of "functional overlay" (Carter, 1967;Florence and Miller, 1985) where a certain proportion of the total presentation is attributed to either 'organic' or 'functional' aetiology, and the wide-ranging discussion of differential diagnosis between syndromes apparently on either side of the aetiological distinction (e.g. Pandey et al, 2014;Pruszewicz et al, 1991;Richter, 1991). These diagnostic categories imply syndromes exist in "purely functional" or "purely organic" equivalents, presumably representing the far ends of a functional-organic spectrum.…”

Section: Discussionmentioning

confidence: 99%

What is the Functional / Organic Distinction Actually Doing in Psychiatry and Neurology?

Bell¹,

Wilkinson²,

Greco³

et al. 2020

Preprint

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The functional-organic distinction aims to distinguish symptoms, signs, and syndromes that can be explained by diagnosable biological changes, from those that cannot. The distinction is central to clinical practice and is a key organising principle in diagnostic systems. Following a pragmatist approach that examines meaning through use, we examine how the functional-organic distinction is deployed and conceptualised in psychiatry and neurology. We note that the conceptual scope of the terms 'functional' and 'organic' varies considerably by context. Techniques for differentially diagnosing 'functional' and 'organic' diverge in the strength of evidence they produce as a necessary function of the syndrome in question. Clinicians do not agree on the meaning of the terms and report using them strategically. The distinction often relies on an implied model of 'zero sum' causality and encourages classification of syndromes into discrete ‘functional’ and ‘organic’ versions. Although this clearly applies in some instances, this is often in contrast to our best scientific understanding of neuropsychiatric disorders as arising from a dynamic interaction between personal, social and neuropathological factors. We also note 'functional' and 'organic' have loaded social meanings, creating the potential for social disempowerment and epistemic injustice. Given this, we argue for a better understanding of how strategic simplification and complex scientific reality limit each other. We also note that the contribution of people who experience the interaction between 'functional' and 'organic' factors has rarely informed the validity of this distinction and the dilemmas arising from it, and we highlight this as a research priority.

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Section: Discussionmentioning

confidence: 99%

What is the Functional / Organic Distinction Actually Doing in Psychiatry and Neurology?

Bell¹,

Wilkinson²,

Greco³

et al. 2020

Preprint

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“…features for the analysis of voice disorders 4) range of Fo (in Hz), (5) noise/lack of noise in vowels, (6) jitter and ( 7) type of intonation course within the utterance.…”

Section: Usefulness Of the Suprasegmentals Speechmentioning

confidence: 99%

“…The target of this investigation was an attempt to find a preliminary acoustic features of voice in groups of patients with organic and functional changes in order to create an algorithm of evaluation of the degree of voice disturbance. It is to a certain degree based on the biophysical assumption that the organic changes usually cause an asymmetric growth of vocal fold mass and that functional changes alter the degree of their tension and coordination ( [ 6 ], [ 9 ]). In this pilot study the investigation included 2 groups of patients: 15 patients with organic changes confined to the glottis and 15 patients with functional voice disturbances in the form of dysphonia hyperfunctionalis.…”

Section: Diagnosis Of Functional and Organic Voice Disordersmentioning

confidence: 99%

Suprasegmental analysis for complex quality assessment in pathological voices

Demenko,

Obrebowski,

Pruszewicz

et al. 2004

Speech Prosody 2004

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Phoniatric and acoustic examinations were carried out in a group of 30 patients with dysphonia, including 15 with organic and 15 with functional dysphonia. Another group of 18 patients with deep hypoacousis was divided into 3 categories: congenital, pre-and post-lingual. Phoniatric and stroboscopy examinations of the larynx was performed in all cases. The differences between functional and organic dysphonia were found after voice fatigue examination. The analysis of the global statistical features of fundamental frequency distribution estimated from the read text as well as the analysis of changes of Fo parameter in individual utterances was applied. The results of this study have been used in more detailed acoustical and perceptual pathological voice analysis.In the other group of 100 patients with organic and functional voice disorders complex voice assessments including extended acoustic-perceptual voice estimation in GRBAS scale as well as classical spectrographic and complex MDVP analysis were performed on appropriate linguistic material including vowels, isolated words and a read text.The importance of complex voice examination is stressed. Voice is a multidimensional phenomena and it cannot be assessed by simple acoustic or phoniatrics methods but only by more complex ones.

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“…이라는 장점이 있다 [3]. 이러한 이유로 음성의 음향학적인 분 석만을 이용해 환자의 음성 장애를 진단하고, 치료 전후의 변 화를 정량적으로 평가하고자 하는 시도는 이미 1990년대 후 반부터 이루어지고 있었다 [4,5].…”

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Artificial Intelligence for Clinical Research in Voice Disease

Seok¹,

Kwon²

2022

J Korean Soc Laryngol Phoniatr Logop

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Diagnosis using voice is non-invasive and can be implemented through various voice recording devices; therefore, it can be used as a screening or diagnostic assistant tool for laryngeal voice disease to help clinicians. The development of artificial intelligence algorithms, such as machine learning, led by the latest deep learning technology, began with a binary classification that distinguishes normal and pathological voices; consequently, it has contributed in improving the accuracy of multi-classification to classify various types of pathological voices. However, no conclusions that can be applied in the clinical field have yet been achieved. Most studies on pathological speech classification using speech have used the continuous short vowel /ah/, which is relatively easier than using continuous or running speech. However, continuous speech has the potential to derive more accurate results as additional information can be obtained from the change in the voice signal over time. In this review, explanations of terms related to artificial intelligence research, and the latest trends in machine learning and deep learning algorithms are reviewed; furthermore, the latest research results and limitations are introduced to provide future directions for researchers.

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Usefulness of Acoustic Studies on the Differential Diagnostics of Organic and Functional Dysphonia

Cited by 9 publications

References 6 publications

What is the Functional / Organic Distinction Actually Doing in Psychiatry and Neurology?

What is the Functional / Organic Distinction Actually Doing in Psychiatry and Neurology?

Suprasegmental analysis for complex quality assessment in pathological voices

Artificial Intelligence for Clinical Research in Voice Disease

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