Smartphone-Based Voice Wellness Index Application for Dysphonia Screening and Assessment: Development and Reliability

Uloza, Virgilijus; Ulozaitė-Stanienė, Nora; Petrauskas, Tadas; Pribuišis, Kipras; Ulozienė, Ingrida; Blažauskas, Tomas; Damaševičius, Robertas; Maskeliūnas, Rytis

doi:10.1016/j.jvoice.2023.10.021

Cited by 3 publications

(3 citation statements)

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“…The “Voice Wellness Index” application for use both with iOS and Android operating devices was utilized for WVI estimation [ 39 ]. This application allows voice recording, automatically extracting acoustic voice features consisting of the AVQI, the GFI measures, and displaying the VWI result alongside a recommendation to the user.…”

Section: Methodsmentioning

confidence: 99%

“…The VWI integrates the voice-related data from two different information sources (i.e., acoustic voice analysis, such as the AVQI and Glottal Function Questionnaire (GFI), as patient-reported outcome measures) and supports the concept that the voice assessment process should consider the multidimensionality involved in the manifestation of voice disorders. The VWI is the equalizing proportion summation of the AVQI and GFI scores [ 39 ]. The VWI scores may range from 0 to 20 points with a higher score indicating more severe dysphonia.…”

Section: Introductionmentioning

confidence: 99%

“…The VWI scores may range from 0 to 20 points with a higher score indicating more severe dysphonia. The results of the recent study showed that VWI application represents an accurate and reliable tool for voice quality measurement and normal versus pathological voice screening, manifesting in excellent diagnostic accuracy (AUC = 0.972) and the best balance between sensitivity (94.15%) and specificity (95.72%) [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

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Accuracy Analysis of the Multiparametric Acoustic Voice Indices, the VWI, AVQI, ABI, and DSI Measures, in Differentiating between Normal and Dysphonic Voices

Uloza,

Pribuišis,

Ulozaite-Staniene

et al. 2023

JCM

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The study aimed to investigate and compare the accuracy and robustness of the multiparametric acoustic voice indices (MAVIs), namely the Dysphonia Severity Index (DSI), Acoustic Voice Quality Index (AVQI), Acoustic Breathiness Index (ABI), and Voice Wellness Index (VWI) measures in differentiating normal and dysphonic voices. The study group consisted of 129 adult individuals including 49 with normal voices and 80 patients with pathological voices. The diagnostic accuracy of the investigated MAVI in differentiating between normal and pathological voices was assessed using receiver operating characteristics (ROC). Moderate to strong positive linear correlations were observed between different MAVIs. The ROC statistical analysis revealed that all used measurements manifested in a high level of accuracy (area under the curve (AUC) of 0.80 and greater) and an acceptable level of sensitivity and specificity in discriminating between normal and pathological voices. However, with AUC 0.99, the VWI demonstrated the highest diagnostic accuracy. The highest Youden index equaled 0.93, revealing that a VWI cut-off of 4.45 corresponds with highly acceptable sensitivity (97.50%) and specificity (95.92%). In conclusion, the VWI was found to be beneficial in describing differences in voice quality status and discriminating between normal and dysphonic voices based on clinical diagnosis, i.e., dysphonia type, implying the VWI’s reliable voice screening potential.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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