How to measure children's feet: 3D foot scanning compared with established 2D manual or digital methods.

BACKGROUND: In infants and young children, a wide heterogeneity of foot shape is typical. Therefore, children, who are additionally influenced by rapid growth and maturation, are a very special cohort for foot measurements and the footwear industry. The importance of foot measurements for footwear fit, design, as well as clinical applications has been sufficiently described. New measurement techniques (3D foot scanning) allow the assessment of the individual foot shape. However, the validity in comparison to conventional methods remains unclear. Therefore, the purpose of this study was to compare 3D foot scanning with two established measurement methods (2D digital scanning/manual foot measurements). METHODS: Two hundred seventy seven children (125 m / 152 f; mean ± SD: 8.0 ± 1.5yrs; 130.2 ± 10.7cm; 28.0 ± 7.3kg) were included into the study. After collection of basic data (sex, age (yrs), body height (cm), body weight (kg)) geometry of the right foot was measured in static condition (stance) with three different measurement systems (fixed order): manual foot measurement, 2D foot scanning (2D desk scanner) and 3D foot scanning (hand-held 3D scanner). Main outcomes were foot length, foot width (projected; anatomical; instep), heel width and anatomical foot ball breadth. Analysis of variances for dependent samples was applied to test for differences between foot measurement methods (Post-hoc analysis: Tukey-Kramer-Test; α=0.05). RESULTS: Significant differences were found for all outcome measures comparing the three methods (p<0.0001). The span of foot length differences ranged from 3 to 6mm with 2D scans showing the smallest and 3D scans the largest deviations. Foot width measurements in comparison of 3D and 2D scans showed consistently higher values for 3D measurements with the differences ranging from 1mm to 3mm. CONCLUSIONS: The findings suggests that when comparing foot data, it is important to consider the differences caused by new measurement methods. Differences of about 0.6cm are relevant when measuring foot length, as this is the difference of a complete shoe size (Parisian point). Hence, correction factors may be required to compare the results of different measurements appropriately. The presented results may have relevance in the field of ergonomics (shoe industry) as well as clinical practice.

Fully automatic segmentation of glottis and vocal folds in endoscopic laryngeal high-speed videos using a deep Convolutional LSTM Network.

The objective investigation of the dynamic properties of vocal fold vibrations demands the recording and further quantitative analysis of laryngeal high-speed video (HSV). Quantification of the vocal fold vibration patterns requires as a first step the segmentation of the glottal area within each video frame from which the vibrating edges of the vocal folds are usually derived. Consequently, the outcome of any further vibration analysis depends on the quality of this initial segmentation process. In this work we propose for the first time a procedure to fully automatically segment not only the time-varying glottal area but also the vocal fold tissue directly from laryngeal high-speed video (HSV) using a deep Convolutional Neural Network (CNN) approach. Eighteen different Convolutional Neural Network (CNN) network configurations were trained and evaluated on totally 13,000 high-speed video (HSV) frames obtained from 56 healthy and 74 pathologic subjects. The segmentation quality of the best performing Convolutional Neural Network (CNN) model, which uses Long Short-Term Memory (LSTM) cells to take also the temporal context into account, was intensely investigated on 15 test video sequences comprising 100 consecutive images each. As performance measures the Dice Coefficient (DC) as well as the precisions of four anatomical landmark positions were used. Over all test data a mean Dice Coefficient (DC) of 0.85 was obtained for the glottis and 0.91 and 0.90 for the right and left vocal fold (VF) respectively. The grand average precision of the identified landmarks amounts 2.2 pixels and is in the same range as comparable manual expert segmentations which can be regarded as Gold Standard. The method proposed here requires no user interaction and overcomes the limitations of current semiautomatic or computational expensive approaches. Thus, it allows also for the analysis of long high-speed video (HSV)-sequences and holds the promise to facilitate the objective analysis of vocal fold vibrations in clinical routine. The here used dataset including the ground truth will be provided freely for all scientific groups to allow a quantitative benchmarking of segmentation approaches in future.

Evaluation of the combined use of narrow band imaging and high-speed imaging to discriminate laryngeal lesions.

BACKGROUND AND OBJECTIVE: Laryngeal lesions are usually investigated by microlaryngoscopy, biopsy, and histopathology. This study aimed to evaluate the combined use of Narrow Band Imaging (NBI) and High-Speed Imaging (HSI) in the differentiation of glottic lesions in awake patients. STUDY DESIGN: Prospective diagnostic study. MATERIALS AND METHODS: Thirty-six awake patients with 41 glottic lesions were investigated with both NBI and HSI, and the suspected diagnoses were compared to the histopathological results of tissue biopsies taken during subsequent microlaryngoscopies. Of the 41 lesions, 28 were primary lesions and 13 recurrent lesions after previous laryngeal pathologies. RESULTS: Sensitivity, specificity, positive predictive value, and negative predictive value in the differentiation between benign/premalignant and malignant lesions with both NBI and HSI accounted to 100.0%, 79.4%, 50.0%, and 100.0%. Sensitivities and specificities were 100.0% and 85.7% for HSI alone, and 100.0% and 79.4% for NBI alone. Regarding only primary lesions the results were generally better with sensitivities and specificities of 100% and 81% for NBI, 100% and 84.2% for HSI and 100% and 85.7% for the combination of both methods, respectively. CONCLUSION: NBI and HSI both seem to be promising adjunct tools in the differentiation of various laryngeal lesions in awake patients with high sensitivities. Specificities, however, were moderate but could be increased when using NBI and HSI in combination in a subgroup of patients with only primary lesions. Although both methods still have limitations they might ameliorate the evaluation of suspicious laryngeal lesions in the future and could possibly spare patients from repeated invasive tissue biopsies. Lasers Surg. Med. 49:609-618, 2017. © 2017 Wiley Periodicals, Inc.

Phasegram Analysis of Vocal Fold Vibration Documented With Laryngeal High-speed Video Endoscopy.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.

A generalized procedure for analyzing sustained and dynamic vocal fold vibrations from laryngeal high-speed videos using phonovibrograms.

OBJECTIVE: This work presents a computer-based approach to analyze the two-dimensional vocal fold dynamics of endoscopic high-speed videos, and constitutes an extension and generalization of a previously proposed wavelet-based procedure. While most approaches aim for analyzing sustained phonation conditions, the proposed method allows for a clinically adequate analysis of both dynamic as well as sustained phonation paradigms. MATERIALS AND METHODS: The analysis procedure is based on a spatio-temporal visualization technique, the phonovibrogram, that facilitates the documentation of the visible laryngeal dynamics. From the phonovibrogram, a low-dimensional set of features is computed using a principle component analysis strategy that quantifies the type of vibration patterns, irregularity, lateral symmetry and synchronicity, as a function of time. Two different test bench data sets are used to validate the approach: (I) 150 healthy and pathologic subjects examined during sustained phonation. (II) 20 healthy and pathologic subjects that were examined twice: during sustained phonation and a glissando from a low to a higher fundamental frequency. In order to assess the discriminative power of the extracted features, a Support Vector Machine is trained to distinguish between physiologic and pathologic vibrations. The results for sustained phonation sequences are compared to the previous approach. Finally, the classification performance of the stationary analyzing procedure is compared to the transient analysis of the glissando maneuver. RESULTS: For the first test bench the proposed procedure outperformed the previous approach (proposed feature set: accuracy: 91.3%, sensitivity: 80%, specificity: 97%, previous approach: accuracy: 89.3%, sensitivity: 76%, specificity: 96%). Comparing the classification performance of the second test bench further corroborates that analyzing transient paradigms provides clear additional diagnostic value (glissando maneuver: accuracy: 90%, sensitivity: 100%, specificity: 80%, sustained phonation: accuracy: 75%, sensitivity: 80%, specificity: 70%). CONCLUSIONS: The incorporation of parameters describing the temporal evolvement of vocal fold vibration clearly improves the automatic identification of pathologic vibration patterns. Furthermore, incorporating a dynamic phonation paradigm provides additional valuable information about the underlying laryngeal dynamics that cannot be derived from sustained conditions. The proposed generalized approach provides a better overall classification performance than the previous approach, and hence constitutes a new advantageous tool for an improved clinical diagnosis of voice disorders.

A noninvasive procedure for early-stage discrimination of malignant and precancerous vocal fold lesions based on laryngeal dynamics analysis.

About two thirds of laryngeal cancers originate at the vocal cords. Early-stage detection of malignant vocal fold alterations, including a discrimination of premalignant lesions, represents a major challenge in laryngology as precancerous vocal fold lesions and small carcinomas are difficult to distinguish by means of regular endoscopy only. We report a procedure to discriminate between malignant and precancerous lesions by measuring the characteristics of vocal fold dynamics by means of a computerized analysis of laryngeal high-speed videos. Ten patients with squamous cell T1a carcinoma, ten with precancerous lesions with hyperkeratosis, and ten subjects without laryngeal disease underwent high-speed laryngoscopy yielding 4,000 images per second. By means of wavelet-based phonovibrographic analysis, a set of three clinically meaningful vibratory measures was extracted from the videos comprising a total number of 15,000 video frames. Statistical analysis (ANOVA with post hoc two-sided t tests, P < 0.05) revealed that vocal fold dynamics is significantly affected in the presence of precancerous lesions and T1a carcinoma. On the basis of the three measures, a discriminating pattern was extracted using a support vector machine-learning algorithm performing an individual classification in respect to the different clinical groups. By applying a leave-one-out cross-validation strategy, we could show that the proposed measures discriminate with a very high performance between precancerous lesions and T1a carcinoma (sensitivity, 100%; specificity, 100%). Although a large-scale study will be necessary to confirm clinical significance, the set of vibratory measures derived in this study may be applicable to improve the accuracy and reliability of noninvasive diagnostics of vocal fold lesions.

Glottal opening and closing events investigated by electroglottography and super-high-speed video recordings.

Previous research has suggested that the peaks in the first derivative (dEGG) of the electroglottographic (EGG) signal are good approximate indicators of the events of glottal opening and closing. These findings were based on high-speed video (HSV) recordings with frame rates 10 times lower than the sampling frequencies of the corresponding EGG data. The present study attempts to corroborate these previous findings, utilizing super-HSV recordings. The HSV and EGG recordings (sampled at 27 and 44 kHz, respectively) of an excised canine larynx phonation were synchronized by an external TTL signal to within 0.037 ms. Data were analyzed by means of glottovibrograms, digital kymograms, the glottal area waveform and the vocal fold contact length (VFCL), a new parameter representing the time-varying degree of 'zippering' closure along the anterior-posterior (A-P) glottal axis. The temporal offsets between glottal events (depicted in the HSV recordings) and dEGG peaks in the opening and closing phase of glottal vibration ranged from 0.02 to 0.61 ms, amounting to 0.24-10.88% of the respective glottal cycle durations. All dEGG double peaks coincided with vibratory A-P phase differences. In two out of the three analyzed video sequences, peaks in the first derivative of the VFCL coincided with dEGG peaks, again co-occurring with A-P phase differences. The findings suggest that dEGG peaks do not always coincide with the events of glottal closure and initial opening. Vocal fold contacting and de-contacting do not occur at infinitesimally small instants of time, but extend over a certain interval, particularly under the influence of A-P phase differences.

Complex vibratory patterns in an elephant larynx.

Elephants' low-frequency vocalizations are produced by flow-induced self-sustaining oscillations of laryngeal tissue. To date, little is known in detail about the vibratory phenomena in the elephant larynx. Here, we provide a first descriptive report of the complex oscillatory features found in the excised larynx of a 25 year old female African elephant (Loxodonta africana), the largest animal sound generator ever studied experimentally. Sound production was documented with high-speed video, acoustic measurements, air flow and sound pressure level recordings. The anatomy of the larynx was studied with computed tomography (CT) and dissections. Elephant CT vocal anatomy data were further compared with the anatomy of an adult human male. We observed numerous unusual phenomena, not typically reported in human vocal fold vibrations. Phase delays along both the inferior-superior and anterior-posterior (A-P) dimension were commonly observed, as well as transverse travelling wave patterns along the A-P dimension, previously not documented in the literature. Acoustic energy was mainly created during the instant of glottal opening. The vestibular folds, when adducted, participated in tissue vibration, effectively increasing the generated sound pressure level by 12 dB. The complexity of the observed phenomena is partly attributed to the distinct laryngeal anatomy of the elephant larynx, which is not simply a large-scale version of its human counterpart. Travelling waves may be facilitated by low fundamental frequencies and increased vocal fold tension. A travelling wave model is proposed, to account for three types of phenomena: A-P travelling waves, 'conventional' standing wave patterns, and irregular vocal fold vibration.

Phonovibrographic wavegrams: visualizing vocal fold kinematics.

Recently, endoscopic high-speed laryngoscopy has been established for commercial use as a state-of-the-art technique to examine vocal fold kinematics. Since modern cameras provide sampling rates of several thousand frames per second, a high volume of data has to be considered for visual and objective analysis. A method for visualizing endoscopic high speed videos in three-dimensional cycle-based graphs combining and extending the approaches of phonovibrograms and electroglottographic wavegrams is presented. To build a phonovibrographic wavegram, individual cycles of a phonovibrogram are segmented, normalized in cycle duration, and concatenated over time. For analyzing purposes, the emerging three-dimensional scalar field is visualized with different rendering techniques providing information of different aspects of vocal fold kinematics. The phonovibrographic wavegram incorporates information about the glottal closure type, size, and location of the amplitudes, symmetry, periodicity, and phase information. The potential of the approach to visualize the characteristics of vocal fold vibration in a compact and intuitive way is demonstrated within two healthy and three pathologic subjects. The phonovibrographic wavegram allows a comprehensive analysis of vocal fold kinematics and reveals information that remains hidden with other visualization techniques.

Vocal fold vibration amplitude, open quotient, speed quotient and their variability along glottal length: kymographic data from normal subjects.

Abstract Quantitative knowledge about healthy vocal fold vibration characteristics provides the basis for an objective assessment of vocal fold vibrations. In this study, using high-speed videolaryngoscopy the alterations of the relative vibration amplitudes, open quotients, and speed quotients were analyzed along the glottal length in 30 male and 30 female healthy subjects. The maximum vibration amplitude was identified at 41.1% ± 10.8% and 46.5% ± 18.0% of the visible glottal length in females and males, respectively. The average open quotients decreased in females and males from posterior to anterior, while the speed quotients did not change systematically. The reported normative values can be used to distinguish normal and abnormal vibrations in clinical practice when aiming at quantitative diagnosis of functional voice disorders.

How low can you go? Physical production mechanism of elephant infrasonic vocalizations.

Elephants can communicate using sounds below the range of human hearing ("infrasounds" below 20 hertz). It is commonly speculated that these vocalizations are produced in the larynx, either by neurally controlled muscle twitching (as in cat purring) or by flow-induced self-sustained vibrations of the vocal folds (as in human speech and song). We used direct high-speed video observations of an excised elephant larynx to demonstrate flow-induced self-sustained vocal fold vibration in the absence of any neural signals, thus excluding the need for any "purring" mechanism. The observed physical principles of voice production apply to a wide variety of mammals, extending across a remarkably large range of fundamental frequencies and body sizes, spanning more than five orders of magnitude.

Vocal fold vibratory behavior changes following surgical treatment of polyps investigated with high-speed videoendoscopy and phonovibrography.

OBJECTIVES: The goal of this study was to objectively quantify the changes in vocal fold vibratory characteristics before and after surgery with high-speed videoendoscopy and the image analysis tool phonovibrography. METHODS: High-speed videoendoscopic data, audio recordings, and Voice Handicap Index scores were collected from 8 subjects with a diagnosis of unilateral vocal fold polyps, before operation and at 1 week and 1 to 3 months after operation. We then analyzed the objective phonovibrographic patterns and parameters describing the vocal fold vibratory behavior. RESULTS: On phonovibrography, the visual representations of the vocal fold vibratory characteristics, from both the individual and the group data, demonstrated very different patterns before surgery and both 1 week and 1 to 3 months after surgery. The individual phonovibrograms obtained from the left and right true vocal folds clearly demonstrated the lesion site and its effects on the vocal fold vibratory characteristics for each subject. The improvements in amplitude and symmetry (relative vibratory amplitude and vibration amplitude symmetry) of vocal fold vibration were quantified; the difference was greatest between data from before surgery and data from 1 week after surgery. CONCLUSIONS: The visual phonovibrographic patterns and quantitative data revealed marked changes in vocal fold vibratory patterns after operation and continued improvement at 1 to 3 months.

Computation of physiological human vocal fold parameters by mathematical optimization of a biomechanical model.

With the use of an endoscopic, high-speed camera, vocal fold dynamics may be observed clinically during phonation. However, observation and subjective judgment alone may be insufficient for clinical diagnosis and documentation of improved vocal function, especially when the laryngeal disease lacks any clear morphological presentation. In this study, biomechanical parameters of the vocal folds are computed by adjusting the corresponding parameters of a three-dimensional model until the dynamics of both systems are similar. First, a mathematical optimization method is presented. Next, model parameters (such as pressure, tension and masses) are adjusted to reproduce vocal fold dynamics, and the deduced parameters are physiologically interpreted. Various combinations of global and local optimization techniques are attempted. Evaluation of the optimization procedure is performed using 50 synthetically generated data sets. The results show sufficient reliability, including 0.07 normalized error, 96% correlation, and 91% accuracy. The technique is also demonstrated on data from human hemilarynx experiments, in which a low normalized error (0.16) and high correlation (84%) values were achieved. In the future, this technique may be applied to clinical high-speed images, yielding objective measures with which to document improved vocal function of patients with voice disorders.

Substitute voice production: quantification of PE segment vibrations using a biomechanical model.

After total larynx excision due to laryngeal cancer, the tracheoesophageal substitute tissue vibrations at the intersection between the pharynx and the esophagus [pharyngoesophageal segment (PE segment)] serve as voice generator. The quality of the substitute voice significantly depends on the vibratory characteristics of the PE segment. For improving voice rehabilitation, the relationship between the PE dynamics and the resulting substitute voice quality is a matter of particular interest. Precondition for a comprehensive analysis of this relationship is an objective quantification of the PE vibrations. For quantification purposes, a method is proposed, which is based on the reproduction of the tissue vibrations by means of a biomechanical model of the PE segment. An optimization procedure for an automatic determination of appropriate model parameters is suggested to adapt the model dynamics to tissue movements extracted from high-speed (HS) videos. The applicability of the optimization procedure is evaluated with ten synthetic data sets. A mean error of 8.2% for the determination of previously defined model parameters was achieved as well as an overall stability of 7.1%. The application of the model to six HS recordings presented a mean correlation of the vibration patterns of 82%.

Objective detection and quantification of mucosal wave propagation.

In this work a detection algorithm for mucosal wave propagation is presented. By incorporating physiological knowledge of mucosal wave properties and taking the segmented lateral movement of both vocal fold edges as a basis, the spatio-temporal position of the traveling mucosal wave is identified and quantitatively captured. The course of mucosal wave propagation can be successfully detected and analyzed with regard to discriminating different types of mucosal wave activity (in terms of spread velocity and symmetry). The preliminary results obtained for six exemplary laryngeal high-speed recordings are promising and demonstrate the potential of the proposed detection and objective description approach.

Clinical value of acoustic voice measures: a retrospective study.

Within this study a retrospective analysis of clinical voice perturbation measures, Dysphonia Severity Index and subjective perceived hoarseness was performed to determine their value under clinical aspects. The study included the data of 580 healthy and 1,700 pathologic voices, which were investigated under the following aspects. The relevant parameters were identified and their interrelation determined. Group differences between healthy and pathologic voices were figured out and investigated if voice quality measures allowed an automatic diagnosis of voice disorders. The analysis revealed significant changes between the clinical groups, which indicate the diagnostic relevance of voice quality measures. However, an individual diagnosis of the underlying voice disorder failed due to a vast spread of the parameter values within the respective groups. Classification accuracies of 75-90% were achieved. The high misclassification rate of up to 25% implied that in voice disorder diagnosis, the individual interpretation of the parameter values has to be done carefully.

Automatic diagnosis of vocal fold paresis by employing phonovibrogram features and machine learning methods.

The clinical diagnosis of voice disorders is based on examination of the rapidly moving vocal folds during phonation (f0: 80-300Hz) with state-of-the-art endoscopic high-speed cameras. Commonly, analysis is performed in a subjective and time-consuming manner via slow-motion video playback and exhibits low inter- and intra-rater reliability. In this study an objective method to overcome this drawback is presented being based on Phonovibrography, a novel image analysis technique. For a collective of 45 normophonic and paralytic voices the laryngeal dynamics were captured by specialized Phonovibrogram features and analyzed with different machine learning algorithms. Classification accuracies reached 93% for 2-class and 73% for 3-class discrimination. The results were validated by subjective expert ratings given the same diagnostic criteria. The automatic Phonovibrogram analysis approach exceeded the experienced raters' classifications by 9%. The presented method holds a lot of potential for providing reliable vocal fold diagnosis support in the future.

Classification of functional voice disorders based on phonovibrograms.

OBJECTIVE: This work presents a computer-aided method for automatically and objectively classifying individuals with healthy and dysfunctional vocal fold vibration patterns as depicted in clinical high-speed (HS) videos of the larynx. METHODS: By employing a specialized image segmentation and vocal fold movement visualization technique - namely phonovibrography - a novel set of numerical features is derived from laryngeal HS videos capturing the dynamic behavior and the symmetry of oscillating vocal folds. In order to assess the discriminatory power of the features, a support vector machine is applied to the preprocessed data with regard to clinically relevant diagnostic tasks. Finally, the classification performance of the learned nonlinear models is evaluated to allow for conclusions to be drawn about suitability of features and data resulting from different examination paradigms. As a reference, a second feature set is determined which corresponds to more traditional voice analysis approaches. RESULTS: For the first time an automatic classification of healthy and pathological voices could be obtained by analyzing the vibratory patterns of vocal folds using phonovibrograms (PVGs). An average classification accuracy of approximately 81% was achieved for 2-class discrimination with PVG features. This exceeds the results obtained through traditional voice analysis features. Furthermore, a relevant influence of phonation frequency on classification accuracy was substantiated by the clinical HS data. CONCLUSION: The PVG feature extraction and classification approach can be assessed as being promising with regard to the diagnosis of functional voice disorders. The obtained results indicate that an objective analysis of dysfunctional vocal fold vibration can be achieved with considerably high accuracy. Moreover, the PVG classification method holds a lot of potential when it comes to the clinical assessment of voice pathologies in general, as the diagnostic support can be provided to the voice clinician in a timely and reliable manner. Due to the observed interdependency between phonation frequency and classification accuracy, in future comparative studies of HS recordings of oscillating vocal folds homogeneous frequencies should be taken into account during examination.

Biomechanical modeling of the three-dimensional aspects of human vocal fold dynamics.

Human voice originates from the three-dimensional (3D) oscillations of the vocal folds. In previous studies, biomechanical properties of vocal fold tissues have been predicted by optimizing the parameters of simple two-mass-models to fit its dynamics to the high-speed imaging data from the clinic. However, only lateral and longitudinal displacements of the vocal folds were considered. To extend previous studies, a 3D mass-spring, cover-model is developed, which predicts the 3D vibrations of the entire medial surface of the vocal fold. The model consists of five mass planes arranged in vertical direction. Each plane contains five longitudinal, mass-spring, coupled oscillators. Feasibility of the model is assessed using a large body of dynamical data previously obtained from excised human larynx experiments, in vivo canine larynx experiments, physical models, and numerical models. Typical model output was found to be similar to existing findings. The resulting model enables visualization of the 3D dynamics of the human vocal folds during phonation for both symmetric and asymmetric vibrations.

The influence of temporal stimulus changes on speech-evoked potentials revealed by approximations of tone-evoked waveforms.

OBJECTIVE: The aim of the study was to determine whether cortical auditory potentials evoked by monosyllabic words beginning with a single consonant can be attributed to a combination of two N1/P2 complexes, temporally separated by voice-onset time (VOT). DESIGN: Cortical auditory-evoked potentials were recorded in seven normal-hearing young adults in response to two types of stimuli (a) simple tone bursts and (b) five monosyllabic words with different VOTs. Cortical burst responses (mainly consisting of N1 and P2) formed the basic functions for the simulation of speech-evoked potentials. Actually, two basic functions were created with respect to different VOTs of the speech sounds. An optimization procedure was used to determine the relative contributions of the two N1/P2 complexes. RESULTS: Speech-evoked potentials differed clearly across the stimuli. In all subjects, close matches of the synthetic and the measured waveforms could be gained for all speech sounds. The relative magnitudes of the constituent complexes differed among stimuli. CONCLUSIONS: The auditory-evoked response to a monosyllabic speech sound with short VOT can be represented by two overlapping N1/P2 complexes-one to syllable onset and the second to vowel onset. The temporal separation between the two components is well predicted by VOT, but the relative amplitudes vary across syllables. Observed variability in the fitting accuracy across subjects is small.