scholarly journals Common mistakes in the diagnosis of laryngeal pathology

2020 ◽  
Vol 19 (2) ◽  
pp. 93-99
Author(s):  
A. I. Kryukov ◽  
◽  
S. G. Romanenko ◽  
O. G. Pavlikhin ◽  
E. V. Lesogorova ◽  
...  
Keyword(s):  
Laryngeal Cancer ◽  
Correct Diagnosis ◽  
Voice Quality ◽  
Voice Disorders ◽  
Voice Disorder ◽  
Laryngeal Diseases ◽  
Root Cause ◽  
Incorrect Diagnosis ◽  
Reinke’S Edema ◽  
Chronic Laryngitis

The article The article describes in detail the main stages of the diagnosis of voice disorders with an indication of the methods and major errors leading to an incorrect diagnosis. Since in some cases, impaired voice quality is the first and/ or only symptom of concomitant diseases of organs or systems of various etiologies, an expanded diagnostic search is required to make a correct diagnosis. The features of receiving of complaints and medical history from patients with laryngeal diseases, the guidelines for laryngoscopy are described. A description of the laryngoscopic vew is presented, which helps in the diagnosis of the initial stages of Reinke’s edema, hyperplastic laryngitis and early stages of laryngeal cancer. The relationship between the functional and organic pathology of the larynx is very close, it can be difficult to understand the root cause of voice disorder, this leads to incorrect treatment tactics, the progression and relapse of the disease. The causes of laryngeal diseases of an organic and functional nature, the features of the clinical picture and the differential diagnosis of voice disorders are considered. Cases of diagnosis, a clinic of chronic laryngitis, laryngomycosis, and laryngeal cancer are described; the main approaches to the treatment of laryngeal diseases are presented. The article will be useful to otorhinolaryngologists, phoniatricians of outpatient and inpatient care.

Determining Medical Urgency of Voice Disorders Using Auditory-Perceptual Voice Assessments Performed by Speech-Language Pathologists

2021 ◽  
pp. 000348942110327
Author(s):  
Robert Brinton Fujiki ◽  
Peter W. Sanders ◽  
M. Preeti Sivasankar ◽  
Stacey Halum
Keyword(s):  
Medical History ◽  
Laryngeal Cancer ◽  
Patient Information ◽  
Voice Quality ◽  
Voice Disorders ◽  
Smoking History ◽  
Voice Disorder ◽  
Speech Language Pathologists ◽  
Laryngeal Paralysis ◽  
History Information

Objective: This study examined whether speech-language pathologist auditory-perceptual voice assessments can predict the medical urgency of voice disorders. Methods: Twenty speech-language pathologists (SLPs) evaluated 25 voice samples recorded during initial voice evaluations. Voice samples represented a range of dysphonia severity (mild-severe) balanced across patient diagnoses. Diagnoses included: benign lesions, laryngeal cancer, non-organic voice disorders, laryngeal edema (associated with LPR), and laryngeal paralysis or paresis. Laryngeal cancer and severe unilateral laryngeal paralysis were considered urgent disorders. While blinded to patient information, SLPs rated severity of voice quality, predicted patient diagnosis, and determined whether the patient should be seen urgently by a laryngologist. SLPs were then given basic medical history information and rated medical urgency of voice disorder a second time. Results: On average, SLPs correctly identified 65% of urgent voices and 87% of nonurgent voices when blinded to patient information. Accuracy improved significantly to 86% for urgent voices with medical history information ( P < .001) and decreased to 77% for nonurgent voices. Accuracy was better when severity of voice quality was severe for urgent voices and mild for nonurgent voices ( P < .001). SLPs indicated that patient smoking history and severity of dysphonia were most influential in their decision making. Diagnostic accuracy of auditory-perceptual assessments was poor. Conclusions: SLPs identified 86% of medically urgent voice disorders when auditory perceptual assessments were combined with medical history information. Further work is needed to determine what medical history information is most crucial to rating accuracy and what speech tasks might best separate urgent and nonurgent patients.

scholarly journals Multivariate Analysis of Vocal Fold Vibrations on Various Voice Disorders Using High-Speed Digital Imaging

2021 ◽  
Vol 11 (14) ◽  
pp. 6284
Author(s):  
Akihito Yamauchi ◽  
Hiroshi Imagawa ◽  
Hisayuki Yokonishi ◽  
Ken-Ichi Sakakibara ◽  
Niro Tayama
Keyword(s):  
Multivariate Analysis ◽  
Digital Imaging ◽  
Vocal Fold ◽  
High Speed ◽  
Voice Disorders ◽  
Normal Subjects ◽  
Voice Disorder ◽  
Coefficient Of Determination ◽  
Laryngeal Diseases ◽  
Disease Specific

Although many quantitative parameters have been devised to describe abnormalities in vocal fold vibration, little is known about the priority of these parameters. We conducted a prospective study using high-speed digital imaging to elucidate disease-specific key parameters (KPs) to characterize the vocal fold vibrations of individual voice disorders. From 304 patients with various voice disorders and 46 normal speakers, high-speed digital imaging of a sustained phonation at a comfortable pitch and loudness was recorded and parameters from visual-perceptual rating, laryngotopography, digital kymography, and glottal area waveform were calculated. Multivariate analysis was then applied to these parameters to elucidate the KPs to explain each voice disorder in comparison to normal subjects. Four key parameters were statistically significant for all laryngeal diseases. However, the coefficient of determination (R2) was very low (0.29). Vocal fold paralysis (8 KPs, R2 = 0.76), sulcus vocalis (4 KPs, R2 = 0.74), vocal fold scarring (1 KP, R2 = 0.68), vocal fold atrophy (6 KPs, R2 = 0.53), and laryngeal cancer (1 KP, R2 = 0.52) showed moderate-to-high R2 values. The results identified different KPs for each voice disorder; thus, disease-specific analysis is a reasonable approach.

A Deep Learning Approach for Voice Disorder Detection for Smart Connected Living Environments

2022 ◽  
Vol 22 (1) ◽  
pp. 1-16
Author(s):  
Laura Verde ◽  
Nadia Brancati ◽  
Giuseppe De Pietro ◽  
Maria Frucci ◽  
Giovanna Sannino
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Deep Learning ◽  
Mobile Devices ◽  
Voice Quality ◽  
Voice Disorders ◽  
Computation Time ◽  
Voice Disorder ◽  
Process Data ◽  
Mobile Health Application

Edge Analytics and Artificial Intelligence are important features of the current smart connected living community. In a society where people, homes, cities, and workplaces are simultaneously connected through various devices, primarily through mobile devices, a considerable amount of data is exchanged, and the processing and storage of these data are laborious and difficult tasks. Edge Analytics allows the collection and analysis of such data on mobile devices, such as smartphones and tablets, without involving any cloud-centred architecture that cannot guarantee real-time responsiveness. Meanwhile, Artificial Intelligence techniques can constitute a valid instrument to process data, limiting the computation time, and optimising decisional processes and predictions in several sectors, such as healthcare. Within this field, in this article, an approach able to evaluate the voice quality condition is proposed. A fully automatic algorithm, based on Deep Learning, classifies a voice as healthy or pathological by analysing spectrogram images extracted by means of the recording of vowel /a/, in compliance with the traditional medical protocol. A light Convolutional Neural Network is embedded in a mobile health application in order to provide an instrument capable of assessing voice disorders in a fast, easy, and portable way. Thus, a straightforward mobile device becomes a screening tool useful for the early diagnosis, monitoring, and treatment of voice disorders. The proposed approach has been tested on a broad set of voice samples, not limited to the most common voice diseases but including all the pathologies present in three different databases achieving F1-scores, over the testing set, equal to 80%, 90%, and 73%. Although the proposed network consists of a reduced number of layers, the results are very competitive compared to those of other “cutting edge” approaches constructed using more complex neural networks, and compared to the classic deep neural networks, for example, VGG-16 and ResNet-50.

Characteristics of swallowing disorders in patients with dysphonia

2019 ◽  
Vol 73 (6) ◽  
pp. 1-5
Author(s):  
Paulina Krasnodębska ◽  
Agata Szkiełkowska ◽  
Agnieszka Jarzyńska-Bućko ◽  
Elżbieta Włodarczyk ◽  
Beata Miaśkiewicz
Keyword(s):  
Voice Disorders ◽  
Maximum Amplitude ◽  
Underlying Disease ◽  
Swallowing Disorders ◽  
Voice Disorder ◽  
Swallowing Dysfunction ◽  
Swallowing Problems ◽  
History Of ◽  
Speech Therapist ◽  
Chronic Laryngitis

Introduction Coexistence of dysphagia with voice disorders is a topic rarely raised in the literature. Particular attention is paid to the aspect of muscle dysfunction of the throat and larynx. Aim The aim of the study was to analyze the cases of patients with dysphonia in terms of coexistence of swallowing dysfunction. Material and method The material of the study included 515 patients hospitalized due to dysphonia in 2018. Patients whose interview indicated swallowing problems were subjected to additional diagnosis for dysphagia (FEES, extended speech therapist examination, SEMG). Results 11.8% of people requiring treatment for voice disorders reported coexistence of swallowing problems. Dysphagia was diagnosed in 9.3%. The percentage of people diagnosed with swallowing dysfunction differed depending on the type of underlying disease and was the highest in the group with neurological disorders. Analysis of the correlation between the severity of dysphagia (according to the assessed grade, DHI, EAT-10 results) and the severity of the VHI showed a weak correlation between VHI and EAT-10 (p = 0.1), statistically significant correlations (p<0,05) between the value of VHI and RSI in people with diagnosed neurological disease, between the value of VHI and DHI in people with hyperfunctional dysphonia and the value of VHI and BMI and EAT- 10 in people with chronic laryngitis. Moreover, statistically significant correlations were found between the severity of dysphagia and EAT-10 and DHI (p <0.05). Speech therapist examination indicated the co-existing problem of non-normative swallowing pattern. The electromyographic study showed the largest asymmetries in recording the average and maximum amplitude from masseters. Conclusions Treatment of patients with voice disorders requires interdisciplinary care. A history of dysphagia in these patients should complement the medical history of voice disorders. The characteristics of swallowing disorders vary depending on the cause of the voice disorder and their co-occurrence affects on average 9.3% of patients. In cases of suspected dysphagia, it is necessary to order an accurate speech therapist examination and then to include diagnostic tests to determine further therapy.

Multiple Perspectives on the Barriers to Identification and Management of Pediatric Voice Disorders

2017 ◽  
Vol 2 (3) ◽  
pp. 49-56
Author(s):  
Jana Childes ◽  
Alissa Acker ◽  
Dana Collins
Keyword(s):  
Academic Success ◽  
Voice Disorders ◽  
School Personnel ◽  
Voice Disorder ◽  
Multiple Perspectives ◽  
Vocal Qualities ◽  
High Prevalence ◽  
Pediatric Populations ◽  
Low Incidence ◽  
University Settings

Pediatric voice disorders are typically a low-incidence population in the average caseload of clinicians working within school and general clinic settings. This occurs despite evidence of a fairly high prevalence of childhood voice disorders and the multiple impacts the voice disorder may have on a child's social development, the perception of the child by others, and the child's academic success. There are multiple barriers that affect the identification of children with abnormal vocal qualities and their access to services. These include: the reliance on school personnel, the ability of parents and caretakers to identify abnormal vocal qualities and signs of misuse, the access to specialized medical services for appropriate diagnosis, and treatment planning and issues related to the Speech-Language Pathologists' perception of their skills and competence regarding voice management for pediatric populations. These barriers and possible solutions to them are discussed with perspectives from the school, clinic and university settings.

scholarly journals Modelling of Amplitude Modulated Vocal Fry Glottal Area Waveforms Using an Analysis-by-Synthesis Approach

2021 ◽  
Vol 11 (5) ◽  
pp. 1990
Author(s):  
Vinod Devaraj ◽  
Philipp Aichinger
Keyword(s):  
Voice Quality ◽  
Low Frequency ◽  
Voice Disorder ◽  
Support Vector ◽  
Svm Classifier ◽  
Power Spectral ◽  
Analysis By Synthesis ◽  
Simple Support ◽  
Frequency Modulations ◽  
Synthesis Approach

The characterization of voice quality is important for the diagnosis of a voice disorder. Vocal fry is a voice quality which is traditionally characterized by a low frequency and a long closed phase of the glottis. However, we also observed amplitude modulated vocal fry glottal area waveforms (GAWs) without long closed phases (positive group) which we modelled using an analysis-by-synthesis approach. Natural and synthetic GAWs are modelled. The negative group consists of euphonic, i.e., normophonic GAWs. The analysis-by-synthesis approach fits two modelled GAWs for each of the input GAW. One modelled GAW is modulated to replicate the amplitude and frequency modulations of the input GAW and the other modelled GAW is unmodulated. The modelling errors of the two modelled GAWs are determined to classify the GAWs into the positive and the negative groups using a simple support vector machine (SVM) classifier with a linear kernel. The modelling errors of all vocal fry GAWs obtained using the modulating model are smaller than the modelling errors obtained using the unmodulated model. Using the two modelling errors as predictors for classification, no false positives or false negatives are obtained. To further distinguish the subtypes of amplitude modulated vocal fry GAWs, the entropy of the modulator’s power spectral density and the modulator-to-carrier frequency ratio are obtained.

A High Prevalence of Affective Disorder Discovered in a ‘Schizophrenia Clinic’

1977 ◽  
Vol 22 (4) ◽  
pp. 181-183 ◽  
Author(s):  
Morton S. Rapp ◽  
Peggy Edwards
Keyword(s):  
Affective Disorder ◽  
Affective Disorders ◽  
Correct Diagnosis ◽  
Lithium Carbonate ◽  
Case Histories ◽  
Clinical Notes ◽  
The Past ◽  
High Prevalence ◽  
Incorrect Diagnosis

Fifty outpatients in a ‘schizophrenia clinic’ were examined, and sixteen were found to be suffering from periodic affective disorders. Nine of these were given lithium carbonate, and eight responded well. Case histories illustrate three separate reasons for incorrect diagnosis. Examination of extensive old clinical notes of five of these patients suggests that the problems of diagnosis which have been described in the literature in the past, continue to represent obstacles to correct diagnosis. Suggestions for improvement are offered.

Interaction of Speech Coders and Atypical Speech II

2002 ◽  
Vol 45 (4) ◽  
pp. 689-699 ◽  
Author(s):  
Donald G. Jamieson ◽  
Vijay Parsa ◽  
Moneca C. Price ◽  
James Till
Keyword(s):  
Communication Systems ◽  
Speech Rate ◽  
Voice Quality ◽  
Voice Disorders ◽  
Normal Hearing ◽  
Speech Quality ◽  
Degraded Speech ◽  
Before And After ◽  
Subband Processing

We investigated how standard speech coders, currently used in modern communication systems, affect the quality of the speech of persons who have common speech and voice disorders. Three standardized speech coders (GSM 6.10 RPELTP, FS1016 CELP, and FS1015 LPC) and two speech coders based on subband processing were evaluated for their performance. Coder effects were assessed by measuring the quality of speech samples both before and after processing by the speech coders. Speech quality was rated by 10 listeners with normal hearing on 28 different scales representing pitch and loudness changes, speech rate, laryngeal and resonatory dysfunction, and coder-induced distortions. Results showed that (a) nine scale items were consistently and reliably rated by the listeners; (b) all coders degraded speech quality on these nine scales, with the GSM and CELP coders providing the better quality speech; and (c) interactions between coders and individual voices did occur on several voice quality scales.

Voice Disorders in Obstructive Sleep Apnea: Prevalence, Risk Factors, and the Role of CPAP

2018 ◽  
Vol 128 (3) ◽  
pp. 249-262 ◽  
Author(s):  
Nelson Roy ◽  
Ray M. Merrill ◽  
Jenny Pierce ◽  
Krishna M. Sundar
Keyword(s):  
Quality Of Life ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Voice Disorders ◽  
Acid Reflux ◽  
Voice Disorder ◽  
Apnea Hypopnea Index ◽  
Obstructive Sleep ◽  
A Current

Objective: Obstructive sleep apnea (OSA) is characterized by frequent interruptions in breathing related to upper airway collapse during sleep and may adversely affect phonatory function. This study aimed to: (1) establish the prevalence, risks, and quality of life burden of voice disorders in OSA and (2) explore the relation between voice disorders and positive airway pressure (PAP) therapy. Study Design: Cross-sectional, descriptive epidemiology study. Methods: Analyses were based on 94 individuals with OSA (53 men, 41 women; mean age = 54.7 ± 12.8 years) who completed a telephone interview. Results: Twenty-eight percent of participants reported having a current voice disorder. Of those with a current voice disorder, 83% had experienced symptoms for at least a year, and 58% had symptoms for at least 4 years. The prevalence of a current voice disorder was greater in women than men (44% vs 15%, P = .0020) but did not vary significantly across different age groups, body mass index (BMI), apnea/hypopnea index (AHI) severity, or medical history. After adjusting for sex, consistent use of PAP therapy (with humidification) was associated with (1) lower occurrence of voice disorders in women (Mantel-Haenszel [MH] χ2 P = .0195), (2) reduced snoring severity accompanied by fewer voice disorders in men (MH χ2 P = .0101), and (3) fewer reports of acid reflux as a possible trigger for voice problems (MH χ2 P = .0226). Patients with OSA who also had a current voice disorder experienced lower overall quality of life compared to those without. Conclusions: Chronic, longstanding voice disorders are common in women with OSA and produce significant adverse effects on quality of life. Nightly PAP use (with humidification) was associated with fewer voice symptoms and reduced severity of snoring and acid reflux as possible contributors. Further research is necessary to better understand the origin of these voice disorders in OSA and their potential response to treatment.

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