Document Type
Article
Publication Date
1-1-2020
Abstract
Background: Various voice assessment tools, such as questionnaires and aerodynamic voice characteristics, can be used to assess vocal function of individuals. However, not much is known about the best combinations of these parameters in identification of functional dysphonia in clinical settings. Methods: This study investigated six scores from clinically commonly used questionnaires and seven acoustic parameters. 514 females and 277 males were analyzed. The subjects were divided into three groups: one healthy group (N01) (49 females, 50 males) and two disordered groups with perceptually hoarse (FD23) (220 females, 96 males) and perceptually not hoarse (FD01) (245 females, 131 males) sounding voices. A tree stumps Adaboost approach was applied to find the subset of parameters that best separates the groups. Subsequently, it was determined if this parameter subset reflects treatment outcome for 120 female and 51 male patients by pairwise pre-and post-treatment comparisons of parameters. Results: The questionnaire 'Voice-related-quality-of-Life' and three objective parameters ('maximum fundamental frequency', 'maximum Intensity' and 'Jitter Percent') were sufficient to separate the groups (accuracy ranging from 0.690 (FD01 vs. FD23, females) to 0.961 (N01 vs. FD23, females)). Our study suggests that a reduced parameter subset (4 out of 13) is sufficient to separate these three groups. All parameters reflected treatment outcome for patients with hoarse voices, Voice-related-quality-of-Life showed improvement for the not hoarse group (FD01). Conclusion: Results show that single parameters are insufficient to separate voice disorders but a set of several well-chosen parameters is. These findings will help to optimize and reduce clinical assessment time.
Publication Source (Journal or Book title)
IEEE Journal of Translational Engineering in Health and Medicine
Recommended Citation
Schlegel, P., Kist, A., Semmler, M., Dollinger, M., Kunduk, M., Durr, S., & Schutzenberger, A. (2020). Determination of Clinical Parameters Sensitive to Functional Voice Disorders Applying Boosted Decision Stumps. IEEE Journal of Translational Engineering in Health and Medicine, 8 https://doi.org/10.1109/JTEHM.2020.2985026