Study of finite element modeling from CT images.

The use of finite element analysis is becoming more widespread with rapid advancements in computer technology. However, the field of dentistry is not enjoying the spillover benefits of the expanded use of this design simulation and analysis tool. Finite element modeling requires measurement of the object. However, as the living body is morphologically very complex, this requires a great deal of both time and skill using CAD applications, thus preventing its widespread adoption in the dental field. Although there have been reports of finite element modeling from CT images, these methods require skilled programmers for software development--which is another factor that prevents its widespread adoption in dentistry. Therefore, establishing a finite element modeling method that is both accurate and practical will be of great benefit in clinical dentistry. In the present study, a method using computer tomography and existing software was examined for finite element model construction based on computer tomography images. The results suggested that the method developed here is feasible and practical for clinical use.

Application of neural network to humanoid robots-development of co-associative memory model.

We have been studying a system of many harmonic oscillators (neurons) interacting via a chaotic force since 2002. Each harmonic oscillator is driven by chaotic force whose bifurcation parameter is modulated by the position of the harmonic oscillator. Moreover, a system of mutually coupled chaotic neural networks was investigated. Different patterns were stored in each network and the associative memory problem was discussed in these networks. Each network can retrieve the pattern stored in the other network. On the other hand, we have been developing new mechanisms and functions for a humanoid robot with the ability to express emotions and communicate with humans in a human-like manner. We introduced a mental model which consisted of the mental space, the mood, the equations of emotion, the robot personality, the need model, the consciousness model and the behavior model. This type of mental model was implemented in Emotion Expression Humanoid Robot WE-4RII (Waseda Eye No.4 Refined II). In this paper, an associative memory model using mutually coupled chaotic neural networks is proposed for retrieving optimum memory (recognition) in response to a stimulus. We implemented this model in Emotion Expression Humanoid Robot WE-4RII (Waseda Eye No.4 Refined II).

Mechanical strain on the human skull in a humanoid robotic model.

Patterns of strain were analyzed in a dry human skull at 15 different regions on the lateral and medial surfaces of the mandible. The strains were induced with a human robotic system that represented each of 8 bilateral muscles by a DC servomotor connected to a wire and pulley. The tractions of the simulated muscles (masseter, medial pterygoid, anterior temporalis, and posterior temporalis) were increased from 1x to 4x with each representing different levels of traction or force (5, 3, 4, and 4 N, respectively). The study was done with the teeth in maximum intercuspal occlusion. Bite forces were also measured with a transducer and reached a maximum of 40 N on the posterior teeth with less force on the anterior dentition. The smallest traction level (1x) developed some small strains. At 2x, compressive strains developed more on the medial (lingual) side beneath the molars through the corpus and radiated into the anterior ramus. Strains at 3x to 4x significantly increased both the tensile and compressive strains throughout the mandible with more strains developing in the ramus. The increased bilateral traction and loading developed significant compressive forces on both sides of the mandible. Evaluation of disparities between compressive and tensile strains at one site, and comparison between the medial and lateral sides of strain, suggested some visible distortion of portions of the mandible under the higher loads.