Objective Prephonatory vocal fold angle trajectories may supply useful information about the laryngeal system but were examined in previous studies using sigmoidal curves fit to data collected at 30 frames per second (fps). Here, high-speed videoendoscopy (HSV) was used to investigate the impacts of video frame rate and sigmoidal fitting strategy on vocal fold adductory patterns for voicing onsets. Method Twenty-five participants with healthy voices performed /ifi/ sequences under flexible nasendoscopy at 1,000 fps. Glottic angles were extracted during adduction for voicing onset; resulting vocal fold trajectories (i.e., changes in glottic angle over time) were down-sampled to simulate different frame rate conditions (30–1,000 fps). Vocal fold adduction data were fit with asymmetric sigmoids using 5 fitting strategies with varying parameter restrictions. Adduction trajectories and maximum adduction velocities were compared between the fits and the actual HSV data. Adduction trajectory errors between HSV data and fits were evaluated using root-mean-square error and maximum angular velocity error. Results Simulated data were generally well fit by sigmoid models; however, when compared to the actual 1,000-fps data, sigmoid fits were found to overestimate maximum angle velocities. Errors decreased as frame rate increased, reaching a plateau by 120 fps. Conclusion In healthy adults, vocal fold kinematic behavior during adduction is generally sigmoidal, although such fits can produce substantial errors when data are acquired at frame rates lower than 120 fps.

Multimodal, molecular imaging allows the visualization of biological processes at cellular, subcellular, and molecular-level resolutions using multiple, complementary imaging techniques. These imaging agents facilitate the real-time assessment of pathways and mechanisms in vivo, which enhance both diagnostic and therapeutic efficacy. This article presents the protocol for the synthesis of biofunctionalized Prussian blue nanoparticles (PB NPs)--a novel class of agents for use in multimodal, molecular imaging applications. The imaging modalities incorporated in the nanoparticles, fluorescence imaging and magnetic resonance imaging (MRI), have complementary features. The PB NPs possess a core-shell design where gadolinium and manganese ions incorporated within the interstitial spaces of the PB lattice generate MRI contrast, both in T1 and T2-weighted sequences. The PB NPs are coated with fluorescent avidin using electrostatic self-assembly, which enables fluorescence imaging. The avidin-coated nanoparticles are modified with biotinylated ligands that confer molecular targeting capabilities to the nanoparticles. The stability and toxicity of the nanoparticles are measured, as well as their MRI relaxivities. The multimodal, molecular imaging capabilities of these biofunctionalized PB NPs are then demonstrated by using them for fluorescence imaging and molecular MRI in vitro.

No abstract

Relative fundamental frequency (RFF) is a promising acoustic measure for evaluating voice disorders. Yet, the accuracy of the current RFF algorithm varies across a broad range of vocal signals. The authors investigated how fundamental frequency (fo) estimation and sample characteristics impact the relationship between manual and semi-automated RFF estimates. Acoustic recordings were collected from 227 individuals with and 256 individuals without voice disorders. Common fo estimation techniques were compared to the autocorrelation method currently implemented in the RFF algorithm. Pitch strength-based categories were constructed using a training set (1158 samples), and algorithm thresholds were tuned to each category. RFF was then computed on an independent test set (291 samples) using category-specific thresholds and compared against manual RFF via mean bias error (MBE) and root-mean-square error (RMSE). Auditory-SWIPE′ for fo estimation led to the greatest correspondence with manual RFF and was implemented in concert with category-specific thresholds. Refining fo estimation and accounting for sample characteristics led to increased correspondence with manual RFF [MBE = 0.01 semitones (ST), RMSE = 0.28 ST] compared to the unmodified algorithm (MBE = 0.90 ST, RMSE = 0.34 ST), reducing the MBE and RMSE of semi-automated RFF estimates by 88.4% and 17.3%, respectively.

Purpose We empirically assessed the results of computational optimization and prediction in communication interfaces that were designed to allow individuals with severe motor speech disorders to select phonemes and generate speech output. Method Interface layouts were either random or optimized, in which phoneme targets that were likely to be selected together were located in proximity. Target sizes were either static or predictive, such that likely targets were dynamically enlarged following each selection. Communication interfaces were evaluated by 36 users without motor impairments using an alternate access method. Each user was assigned to 1 of 4 interfaces varying in layout and whether prediction was implemented (random/static, random/predictive, optimized/static, optimized/predictive) and participated in 12 sessions over a 3-week period. Six participants with severe motor impairments used both the optimized/static and optimized/predictive interfaces in 1–2 sessions. Results In individuals without motor impairments, prediction provided significantly faster communication rates during training (Sessions 1–9), as users were learning the interface target locations and the novel access method. After training, optimization acted to significantly increase communication rates. The optimization likely became relevant only after training when participants knew the target locations and moved directly to the targets. Participants with motor impairments could use the interfaces with alternate access methods and generally rated the interface with prediction as preferred. Conclusions Optimization and prediction led to increases in communication rates in users without motor impairments. Predictive interfaces were preferred by users with motor impairments. Future research is needed to translate these results into clinical practice. Supplemental Material https://doi.org/10.23641/asha.8636948