An iOS-based VoiceScreen application: feasibility for use in clinical settings-a pilot study.

Objectives: To elaborate the application suitable for smartphones for estimation of Acoustic Voice Quality Index (AVQI) and evaluate its usability in the clinical setting.
Methods: An elaborated AVQI automatization and background noise monitoring functions were implemented into a mobile "VoiceScreen" application running the iOS operating system. A study group consisted of 103 adult individuals with normal voices (n = 30) and 73 patients with pathological voices. Voice recordings were performed in the clinical setting with "VoiceScreen" app using iPhone 8 microphones. Voices of 30 patients were recorded before and 1 month after phonosurgical intervention. To evaluate the diagnostic accuracy differentiating normal and pathological voice, the receiver-operating characteristic statistics, i.e., area under the curve (AUC), sensitivity and specificity, and correct classification rate (CCR) were used.
Results: A high level of precision of AVQI in discriminating between normal and dysphonic voices was yielded with corresponding AUC = 0.937. The AVQI cutoff score of 3.4 demonstrated a sensitivity of 86.3% and specificity of 95.6% with a CCR of 89.2%. The preoperative mean value of the AVQI [6.01(SD 2.39)] in the post-phonosurgical follow-up group decreased to 2.00 (SD 1.08). No statistically significant differences (p = 0.216) between AVQI measurements in a normal voice and 1-month follow-up after phonosurgery groups were revealed.
Conclusions: The "VoiceScreen" app represents an accurate and robust tool for voice quality measurement and demonstrates the potential to be used in clinical settings as a sensitive measure of voice changes across phonosurgical treatment outcomes.
(© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)