## Materials and Methods
### Data Analysis  
The proximal pressure sensor of the ISP probe was considered to be in the strike zone of vocal fold collision when the intraglottal pressure signal exhibited the three expected characteristics observed in the literature (e.g., [13]): an impulsive peak at the start of the closed phase, rounded peak during the open phase, and minimum value around zero immediately preceding the impulsive peak of the subsequent phonatory cycle. For phonatory segments exhibiting vocal fold collision, the peak collision pressure was defined as the maximum pressure value for each cycle. The mean subglottal pressure was computed from the simultaneously recorded signal of the distal pressure sensor of the ISP probe. The fundamental frequency of the intraglottal pressure waveform was computed using an autocorrelation-based method designed to process acoustic voice signals [44]. Vocal sound pressure level was computed from the root mean square of the calibrated acoustic microphone signal in dB SPL at 15 cm from the lips. Two numerical modeling approaches were applied to validate their estimates of vocal fold collision pressure given the glottal area waveform and/or vocal fold kinematics derived from the high-speed videoendoscopy data. The first numerical approach employed a Hertzian impact model to estimate vocal fold collision pressures using vocal fold edge  
Figure 3: One phonatory cycle is displayed from the high-speed videoendoscopy data (2000 frames per second) during which the intraglottal pressure sensor of the ISP probe was deemed to be in the strike zone of the left vocal fold. Sixteen frames (frame indices indicated) are shown for the phonatory cycle that was 8 ms in duration, translating to a fundamental frequency of tissue oscillation of 125 Hz. and glottal area contour analysis, referred to as contact pressure analysis (see [45] for algorithmic details). This approach took vocal fold kinematic information extracted from laryngeal high-speed videoendoscopic data as input only. A Kalman filter scheme linked the vocal fold edge motion with a lumped-mass representation of vocal fold tissue contact mechanics. The lumped-mass model was used to estimate the non-physical overlap in the Hertz contact model associated with the deformation of two colliding cylinders. For both consistency and simplicity, the vibrating tissue of each vocal fold edge was represented by a parabola, with anterior and posterior anchor points that were selected for each vocal fold. Given that the tip of the ISP probe rested on the right vocal fold of the participant in this study (blocking the visualization of the vocal fold; see Figure 3), manual adjustment of the anchor points was performed such that the vibrating tissue of the left vocal fold collided at the probe location. Even though this contact pressure analysis method was originally designed to produce normalized contact pressure values, results in physical units were obtained by applying generic material properties for the vocal fold tissue, an effective Young's modulus of 24.75 kPa, and a Poisson ratio of 0.5 [45]. Note that this approach only provides point estimates of the peak vocal fold collision pressure. Alternative models are necessary to yield confidence intervals on these point estimates, as well as estimates of other important vocal function measures. The second mathematical model accomplished the goal of deriving vocal fold collision pressure and other hard-to-measure physiological measures, such as subglottal pressure, glottal airflow, and intrinsic muscle activation levels. This model utilized a Bayesian estimation technique to analyze the spatially calibrated glottal area waveform to derive time-varying signals and confidence intervals for vocal fold collision pressure and these other physiological measures (see [46] for algorithmic details). This approach was based on a subject-specific, body-cover model of the vocal folds [47] and an extended Kalman filter with the glottal area waveform as the only observation signal, i.e., Case I in [PERSON] et al. [46].