voice disorders
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2022 ◽  
Vol 22 (1) ◽  
pp. 1-16
Author(s):  
Laura Verde ◽  
Nadia Brancati ◽  
Giuseppe De Pietro ◽  
Maria Frucci ◽  
Giovanna Sannino

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.


Author(s):  
Eleonora M. C. Trecca ◽  
Ciro Lucio Vigliaroli ◽  
Brandon Kim ◽  
Vincenza Galeano ◽  
Francesca Cavalluzzo ◽  
...  

2022 ◽  
Vol 13 (1) ◽  
pp. 142-145
Author(s):  
Rishikesh Thakur ◽  
Abishesh Jha ◽  
Sanjeev Kumar Thakur

Background: Change in voice is one of the most common complains among patients visiting to ENT outpatient. The causes are numerous and need to be evaluated before approaching to curative intent of treatment. Aims and Objectives: The current study was designed with an aim to analyze the spectrum of voice disorders and their management option. Materials and Methods: Prospective study conducted between June 25, 2020, and November 30, 2021. Clinical, demographic profiles were recorded. Fiber-optic laryngoscopy was performed in all the cases. Radiology examination computed tomography/magnetic resonance imaging was supplemented only in required cases. Treatment was executed based of etiological profile analysis. Minimum 3 months follow-up was collected post-therapy. Statistical analysis was performed using Statistical Package for the Social Sciences version 24. Pearson Chi-square test was used for see the association between parameters. P-value was considered significant while being <0.05. Results: Out of 218 patients, the most patients (approx. 70%) occupied in the age group of 30–50 years. There was male predominance (76.6%). Voice change secondary to laryngopharyngeal reflux was seen in 56.4% of cases. Benign vocal fold lesions (nodule/cyst/polyp) were noticed in 26.5% of cases. Malignant lesions were seen in 1.8% of cases. Benign vocal fold lesions (polyp and cyst) were treated by microlaryngeal surgery (MLS). Pre-malignant lesion (leukoplakia) was treated with MLS stripping. Out of four malignant lesions, one was in early stage and underwent supraglottic laryngectomy while others were in advanced stage (T4) and treated by total laryngectomy. Conclusions: Voice disorders comprise wide etiological profile from reflux to malignant lesion. Timely proper evaluation followed by definitive management achieves good treatment outcomes.


Author(s):  
Kyriaki Kyriakou ◽  
Elena Theodorou ◽  
Kakia Petinou ◽  
Ioannis Phinikettos

2021 ◽  
Vol 26 (4) ◽  
pp. 933-943
Author(s):  
Hwa-Young Pyo ◽  
Jae-Yol Lim ◽  
Sung-Eun Lim ◽  
Seung Jin Lee

Objectives: The present study was performed to investigate the effect of voice problems on voice related quality of life in the elderly with, without voice disorders, according to genders by using the Aging Voice Index-Korean version (AVI-KR).Methods: The AVI-KR, a translated original version of the Aging Voice Index (AVI) into Korean and verified for reliability and validity, was implemented with 50 elderly people without voice disorders (normal group) and 76 elderly people with voice disorders (patient group). Statistical difference according to the group (normal and patient group) and gender (male and female) were analyzed by using a 2-way ANOVA.Results: The mean total score of the AVI-KR of the normal group was significantly higher than that of the patient group. All of the normal group participants showed under 11.00, the cut-off score of AVI-KR, but 17.1% of the patient group appeared under the cut-off score. The female group showed higher scores than the male group, but the difference was not significant. Also, the gender difference of patient groups did not show a statistical significance.Conclusion: The voice-related quality of life in elderly people showed significant difference according to presence/absence of pathological vocal fold status, but the gender difference due to aging did not cause a difference in voice-related quality of life. Even pathological status of vocal fold did not guarantee a bad influence on voice-related quality of life. Therefore, the assessment of elderly people’s voice problems should be carried out not only with an examiner or expert-centered objective tools; but also patient-centered ones, including self-reporting questionnaires and evaluation tools specialized for the elderly, should be developed continuously.


Author(s):  
Seung Jin Lee

The auditory-perceptual evaluation of speech-language pathologists (SLP) in patients with voice disorders is often regarded as a touchstone in the multi-dimensional voice evaluation procedures and provides important information not available in other assessment modalities. Therefore, it is necessary for the SLPs to conduct a comprehensive and in-depth evaluation of not only voice but also the overall speech production mechanism, and they often encounter various difficulties in the evaluation process. In addition, SLPs should strive to avoid bias during the evaluation process and to maintain a wide and constant spectrum of severity for each parameter of voice quality. Lastly, it is very important for the SLPs to perform a team approach by documenting and delivering important information pertaining to auditory-perceptual characteristics in an appropriate and efficient way through close communication with the laryngologists.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Ayşegül Zencir Şen ◽  
Bülent Toğram

Phonatory Aerodynamic System (PAS Model 6600) is an evaluation instrument that assesses the effectiveness of surgical interventions, treatments, and therapy for voice disorders. It can be used for the assessment of voice disorders by supporting other perceptual and instrumental methods. It is important to establish normative data, because the use of appropriate norms is necessary for diagnostic and descriptive accuracy. Therefore, this study is aimed primarily at establishing adult normative databases for phonatory aerodynamic measures obtained with the KayPENTAX PAS Model 6600 among healthy adult Turkish speakers and then examining the effect of age, gender, and age-gender interaction variables on these measures. The contribution of the study is considered so important since it will generate normative data for all measurements—except the mean pitch—by the five protocols of PAS for the first time. Two hundred and six healthy Turkish speakers with normal voice (106 women and 100 men) were included in the study and stratified into three age groups. Forty-five phonatory aerodynamic measures across five PAS protocols (vital capacity, maximum sustained phonation, comfortable sustained phonation, variation in sound pressure level, and voicing efficiency) were collected. Age, gender, and age-gender interaction variables were analyzed for 45 PAS parameters. Significant gender and age effect was found for 30 and 19 variables, respectively. Gender-age interaction together was observed for only 6 parameters. Significant differences were not found for the remaining 10 parameters. Significant age and gender effects were observed for 35 phonatory and aerodynamic measures which are essential part of the objective clinical assessment of voice. Consequently, normative data used as reference in voice assessment should be generated according to age and gender differences.


Author(s):  
Rhonda S. Hackworth

The purpose of this literature review was to identify scholarship pertaining to teachers’ vocal health and to discuss implications for music teachers. The review includes studies where researchers have addressed vocal health issues for K–12 teachers of all subjects as well as issues unique to music teachers. Risk factors, measurement, and treatments for teachers’ voice disorders were also explored. Much is written about the prevalence and treatment of voice disorders in the teaching profession, but there is less information about the prevention of the disorders. More research is needed that specifically concentrates on prevention, and vocal hygiene education in teacher training programs should be increased. Education about vocal health is needed, coupled with strategies for ensuring that teachers make the connection between what they learn in vocal hygiene education and how they manage their vocal health on a daily basis.


Author(s):  
Ofer Amir ◽  
Idit Gutman ◽  
Ron J. Baken ◽  
Adi Primov-Fever ◽  
Nitzan Hertzog ◽  
...  

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