Abstract

In a recent publication, the phasegram, a bifurcation diagram over time, has been introduced as an intuitive visualization tool for assessing the vibratory states of oscillating systems. Here, this nonlinear dynamics approach is augmented with quantitative analysis parameters, and it is applied to clinical laryngeal high-speed video (HSV) endoscopic recordings of healthy and pathological phonations. HSV data from a total of 73 females diagnosed as healthy (n = 42), or with functional dysphonia (n = 15) or with unilateral vocal fold paralysis (n = 16), were quantitatively analyzed. Glottal area waveforms (GAW) and left and right hemi-GAWs (hGAW) were extracted from the HSV recordings. Based on Poincaré sections through phase space-embedded signals, two novel quantitative parameters were computed: the phasegram entropy (PE) and the phasegram complexity estimate (PCE), inspired by signal entropy and correlation dimension computation, respectively. Both PE and PCE assumed higher average values (suggesting more irregular vibrations) for the pathological as compared with the healthy participants, thus significantly discriminating healthy group from the paralysis group (P = 0.02 for both PE and PCE). Comparisons of individual PE or PCE data for the left and the right hGAW within each subject resulted in asymmetry measures for the regularity of vocal fold vibration. The PCE-based asymmetry measure revealed significant differences between the healthy group and the paralysis group (P = 0.03). Quantitative phasegram analysis of GAW and hGAW data is a promising tool for the automated processing of HSV data in research and in clinical practice.

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