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Evaluation of the Electroglottographic Signal Variability in Organic and Functional Dysphonia
Andrea Nacci1, Alberto Macerata2, Luca Bastiani3
1ENT, Audiology and Phoniatrics Unit, University Hospital of Pisa, Pisa, Italy; National Institute for Research in Phoniatrics, University of Pisa, Pisa, Italy.
Objectives:
To confirm the data reported in our previous studies on the analysis of the variability of the electroglottographic signal in the pathological voice; to evaluate possible differences in variability between organic and functional pathologies; to identify any distinctive/typical EGG patterns for these pathologies.
Methods:
One hundred twenty-five subjects were enrolled (36 euphonic and 89 pathological: 24 functional dysphonia, 21 bilateral vocal nodules, 23 unilateral polyps and 21 unilateral cysts). All subjects were studied with videolaryngostroboscopy, spectrographic analysis of voice and electroglottography (EGG). The EGG signal variability was then investigated using amplitude-speed combined analysis, by means of a proprietary software algorithm. Amplitude and Speed variation were expressed as a new parameter, the Variability Index (VI), calculated both for the whole EGG signal recorded (VI-tot) and in each phase of the glottic cycle (VI-Q, absolute value; VI-Q%, percentage value).
Results:
In the comparison of VI values between pathological and normal groups, VI-tot and VI-Q2% (which corresponds to the final phase of vocal fold contact) were significantly greater in pathological subjects (P= 0.002). The comparison of VI values among subgroups of the various pathologies showed a difference for VI-tot (P< 0.0001) and VI-Q2% (P= 0.001); this difference was more marked in the cysts than in the functional dysphonia. The cut-off values of VI-tot and VI-Q2% were 0.191 and 18.17%, respectively (sensitivity and specificity 65.2% and 66.7% for VI-tot and 84.3% and 77.8% for VI-Q2%).
Conclusions:
The variability of the EGG signal investigated through the combined analysis of the amplitude and the speed of vibration using a proprietary algorithm software has proved useful not only to distinguish the normal voice from the pathological voice, but also to characterize which phases are more altered in the various voice pathologies studied, both functional and organic. Furthermore, the analysis of the VI parameter allowed to propose cut-off values characterized by a good sensitivity and specificity to discriminate dysphonia from the euphonic voice. Larger groups of patients will be needed to confirm these results.
