A comparison of simulated jaw dynamics in models of segmental mandibular resection versus resection with alloplastic reconstruction.

STATEMENT OF PROBLEM: Composite mandibular resection resulting in mandibular discontinuity can alter jaw motion, occlusal forces, and mastication, whether or not the jaw is reconstructed. The biomechanical events associated with these changes are difficult to assess clinically and, therefore, are not well documented or researched. PURPOSE: The purpose of this study was to model movements of a mandible with a discontinuity defect, and to compare them to movements of a mandible with its continuity restored by alloplastic reconstruction. MATERIAL AND METHODS: Computational models were created with a novel simulation platform. The variables designed into the models included gravity, external forces, and jaw muscle activity. Each jaw was observed at rest, when opened by external force or by muscle drive, and during the generation of unilateral occlusal force on the nonoperated side. Scarring was simulated with springlike forces. Outputs included individual muscle forces and torques, as well as mandibular incisor and condylar motions. RESULTS: Both models displayed plausible resting postures, and jaw opening with deviation toward the defect side when scarring was simulated. Opening caused by downward force on the incisors differed from that due to muscle activation. Jaw rotations during unilateral molar contact on the unaffected side were muscle specific and influenced by mandibular discontinuity. CONCLUSIONS: Plausible jaw movements after hemimandibulectomy and/or alloplastic reconstruction could be predicted by dynamic modeling. The effect of soft tissue forces on jaw posture and movements varied with the condylar support available. In both models, different opening trajectories were produced by external force on the jaw and by jaw muscle activation. Mandibular rotation during unilateral molar contact depended on which muscles were activated, and the availability of bilateral condylar support.

A dynamic model of jaw and hyoid biomechanics during chewing.

Our understanding of human jaw biomechanics has been enhanced by computational modelling, but comparatively few studies have addressed the dynamics of chewing. Consequently, ambiguities remain regarding predicted jaw-gapes and forces on the mandibular condyles. Here, we used a new platform to simulate unilateral chewing. The model, based on a previous study, included curvilinear articular guidance, a mobile hyoid apparatus, and a compressible food bolus. Muscles were represented by Hill-type actuators with drive profiles tuned to produce target jaw and hyoid movements. The cycle duration was 732 ms. At maximum gape, the lower incisor-point was 20.1mm down, 5.8mm posterior, and 2.3mm lateral to its initial, tooth-contact position. Its maximum laterodeviation to the working-side during closing was 6.1mm, at which time the bolus was struck. The hyoid's movement, completed by the end of jaw-opening, was 3.4mm upward and 1.6mm forward. The mandibular condyles moved asymmetrically. Their compressive loads were low during opening, slightly higher on the working-side at bolus-collapse, and highest bilaterally when the teeth contacted. The model's movements and the directions of its condylar forces were consistent with experimental observations, resolving seeming discordances in previous simulations. Its inclusion of hyoid dynamics is a step towards modelling mastication.

Glove-TalkII--a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

Glove-TalkII is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-TalkII uses several input devices (including a Cyberglove, a ContactGlove, a three-space tracker, and a foot pedal), a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. One subject has trained to speak intelligibly with Glove-TalkII. He speaks slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

Glove-talk II - a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

Glove-Talk II is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-Talk II uses several input devices, a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. With Glove-Talk II, the subject can speak slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

Glove-Talk: a neural network interface between a data-glove and a speech synthesizer.

To illustrate the potential of multilayer neural networks for adaptive interfaces, a VPL Data-Glove connected to a DECtalk speech synthesizer via five neural networks was used to implement a hand-gesture to speech system. Using minor variations of the standard backpropagation learning procedure, the complex mapping of hand movements to speech is learned using data obtained from a single ;speaker' in a simple training phase. With a 203 gesture-to-word vocabulary, the wrong word is produced less than 1% of the time, and no word is produced about 5% of the time. Adaptive control of the speaking rate and word stress is also available. The training times and final performance speed are improved by using small, separate networks for each naturally defined subtask. The system demonstrates that neural networks can be used to develop the complex mappings required in a high bandwidth interface that adapts to the individual user.

Headache and sensation seeking.

According to the cognitive theory of sensation seeking, headache sufferers were predicted to score lower than controls on Zuckerman's Sensation Seeking Scale. 26 subjects who experienced chronic headaches scored significantly lower than a group of 26 controls. The relationships between the Sensation Seeking Scale and a number of personality tests are described. Replication of the findings on this scale with headache patients is encouraged as well as exploration of other personality dimensions which show significant relations with sensation seeking.

Simple strategies for inclusion of Voigt effects in infrared cooling rate calculations.

A line shape with rectangular core and nu(-2) wings is shown to be an excellent alias for the Voigt profile when calculating equivalent widths. It leads to closed analytic forms in the commonly employed random models and gives highly accurate ozone cooling rates. An even simpler device for applications where less accurate results are required involves use of the Lorentz profile with a width which does not vanish at zero pressure.