PURPOSE: To model tension asymmetry caused by superior laryngeal nerve paralysis (SLNP) in excised larynges and apply perturbation, nonlinear dynamic, and aerodynamic analyses. METHOD: SLNP was modeled in 8 excised larynges using sutures and weights to mimic cricothyroid (CT) muscle function. Weights were removed from one side to create tension asymmetry, mimicking unilateral SLNP. Two sets of weights were used, 1 light and 1 heavy. Five conditions were evaluated: (a) no tension, (b) symmetrical light tension, (c) asymmetrical light tension, (d) symmetrical heavy tension, and (e) asymmetrical heavy tension. RESULTS: Perturbation parameters were not significantly different across conditions: percent jitter, χ(2)(4) = 3.70, p = .451; percent shimmer, F(4) = 0.95, p = .321. In addition, many measurements were invalid (error values >10). Second-order entropy was significantly different across conditions, F(4) = 5.432, p = .002, whereas correlation dimension was not, F(4) = 0.99, p = .428. Validity of these nonlinear dynamic parameters was demonstrated by low standard deviations. Phonation threshold pressure, χ (2)(4) = 22.50, p < .001, and power, χ (2)(4) = 9.50, p = .05, differed significantly across conditions, whereas phonation threshold flow did not, χ (2)(4) = 4.08, p = .396. CONCLUSIONS: Nonlinear dynamic analysis differentiated between symmetrical and asymmetrical tension conditions, whereas traditional perturbation analysis was less useful in characterizing type 2 or 3 vocal signals. Supplementing acoustic with aerodynamic parameters may help distinguish among laryngeal disorders of neuromuscular origin.
PURPOSE: To model tension asymmetry caused by superior laryngeal nerve paralysis (SLNP) in excised larynges and apply perturbation, nonlinear dynamic, and aerodynamic analyses. METHOD: SLNP was modeled in 8 excised larynges using sutures and weights to mimic cricothyroid (CT) muscle function. Weights were removed from one side to create tension asymmetry, mimicking unilateral SLNP. Two sets of weights were used, 1 light and 1 heavy. Five conditions were evaluated: (a) no tension, (b) symmetrical light tension, (c) asymmetrical light tension, (d) symmetrical heavy tension, and (e) asymmetrical heavy tension. RESULTS: Perturbation parameters were not significantly different across conditions: percent jitter, χ(2)(4) = 3.70, p = .451; percent shimmer, F(4) = 0.95, p = .321. In addition, many measurements were invalid (error values >10). Second-order entropy was significantly different across conditions, F(4) = 5.432, p = .002, whereas correlation dimension was not, F(4) = 0.99, p = .428. Validity of these nonlinear dynamic parameters was demonstrated by low standard deviations. Phonation threshold pressure, χ (2)(4) = 22.50, p < .001, and power, χ (2)(4) = 9.50, p = .05, differed significantly across conditions, whereas phonation threshold flow did not, χ (2)(4) = 4.08, p = .396. CONCLUSIONS: Nonlinear dynamic analysis differentiated between symmetrical and asymmetrical tension conditions, whereas traditional perturbation analysis was less useful in characterizing type 2 or 3 vocal signals. Supplementing acoustic with aerodynamic parameters may help distinguish among laryngeal disorders of neuromuscular origin.
Authors: Veronika Birk; Michael Döllinger; Alexander Sutor; David A Berry; Dominik Gedeon; Maximilian Traxdorf; Olaf Wendler; Christopher Bohr; Stefan Kniesburges Journal: J Acoust Soc Am Date: 2017-03 Impact factor: 1.840