Mitsunori Tada

Development of an optical 2-axis force sensor usable in MRI environments

This paper presents a MR compatible force sensor. Recently, MRI are widely used in various fields, from medical purpose to brain science, and simultaneous measurement of force information enables more precise investigations of obtained images of living tissue. However, conventional metal force sensors which contaminate the true signals of MRI cannot be used in MRI environments. Furthermore, present MR compatible force sensors have limitation in accuracy, dynamic range and multi axis sensibility. In this paper, an optical 2-axis force sensor without any metal and electronic components in the sensing element is developed with photo sensors and optical fibers.

An optical 6-axis force sensor for brain function analysis using fMRI

This paper presents an 6-axis optical force sensor which can be used in fMRI. Recently, fMRIs are widely used for studying human brain function. Simultaneous measurement of brain activity and peripheral information, such as grip force, enables more precise investigations in studies of motor function. However, conventional force sensors cannot be used in fMRI environment, since metal elements generate noise which severely contaminate the signals of fMRI. An optical 2-axis force sensor has been developed using photo sensors and optical fibers by Tada et. al.(2002), that resolved these problems. The developed force sensor removed all magnetic components from the sensing part. It detected minute displacements by measure amount of light and light traveled through the optical fibers. However, there still remain several problems on this optical force sensor. Firstly, the accuracy is not high compared to the conventional force sensors. Secondly, the robustness is not enough against the contact force to the optical fibers. In this paper, the problems concerning to the accuracy and the sensor output stability has been improved by novel methods of fixing fibers and arithmetic circuit. Furthermore, an optical 6-axis force sensor is developed based on these improvements, and usefulness of our sensor for brain function analysis is confirmed in fMRI experimentations.

An imaging system of incipient slip for modelling how human perceives slip of a fingertip

This paper presents the structure and performance of the newly developed fingerprint imaging system, and the outline of the image processing for the quantification of incipient slip. Incipient slip, that is considered to have direct relation with slip perception, is visualized as distortion of a fingerprint pattern. A force sensor for the contact force measurements are also newly developed. Thus this system enables highly accurate incipient slip and fingertip contact force measurements.

Design of an MR-compatible three-axis force sensor

This paper presents a newly designed and developed MR-compatible three-axis force sensor: its principle, structure and performance. It employs a new MR-compatible optical micrometry based on differential measure of light intensity. This technology enables highly accurate and sensitive two degrees-of-freedom displacement sensing by using optoelectronic devices and pair of fiber optics. In order to realize three-axis force sensitivity, two micrometers are aligned in orthogonal directions. The accuracy of this force sensor is better than 3.0% and the maximum displacement of the detector is about 40 /spl mu/m under the applied force ranging from 0 to 15 N in vertical, and -8 to 8 N in horizontal directions. The loss of homogeneity of the magnetic field and signal-to-noise ratio of the MR image caused by this sensor are observed to be 0.49 ppm and 0.49 to 7.30% that show the sufficient MR compatibility of this sensor.

Stretchable Strain Sensor Based on Areal Change of Carbon Nanotube Electrode

Conventional strain sensors measure strains exerted on solid metals and have been widely applied. Stretch measurements of flexible objects require strain sensors with wide dynamic range (stretch exceeding 100%) that can also measure areal changes. Flexible strain sensors are expected to realize a wide range of technologies, such as human interfaces, smart clothes, skin-motion monitoring, and robotic skin. Recently, carbon nanotubes (CNTs) have been assembled into stretchable conductors, and are potential base materials for various flexible sensors. Herein, we construct a flexible stretching sensor from urethane elastomer and conductive electrodes from singlewalled CNTs. This sensor is extremely thin (thickness: 150 μm), and characterized by high elasticity (up to 100%), low stress (0.8 MPa at 100%), durability (1000 cycles at 50%), light weight (approx. 1.1 g/cm3), and sensitivity (1 pF/mm2). The strain sensor is tested on a cloth fabric, and is confirmed to measure the stretch area of flexible materials.

Material properties estimation of layered soft tissue based on MR observation and iterative FE simulation

In order to calculate deformation of soft tissue under arbitrary loading conditions, we have to take both non-linear material characteristics and subcutaneous structures into considerations. The estimation method of material properties presented in this paper accounts for these issues. It employs a compression test inside MRI in order to visualize deformation of hypodermic layered structure of living tissue, and an FE model of the compressed tissue in which non-linear material model is assigned. The FE analysis is iterated with updated material constant until the difference between the displacement field observed from MR images and calculated by FEM is minimized. The presented method has been applied to a 3-layered silicon rubber phantom. The results show the excellent performance of our method. The accuracy of the estimation is better than 15%, and the reproducibility of the deformation is better than 0.4 mm even for an FE analysis with different boundary condition.

An MR-Compatible Optical Force Sensor for Human Function Modeling

This paper presents the principle, structure and performance of a newly developed MR-compatible force sensor. It employs a new optical micrometry that enables highly accurate and highly sensitive displacement measurement. The sensor accuracy is better than 1.0 %, and the maximum displacement of the detector is about 10 μm for a range of the applied force from 0 to 6 N.

Reconstructing individual hand models from motion capture data

In this paper, we propose a new method of reconstructing the hand models for individuals, which include the link structure models, the homologous skin surface models and the homologous tetrahedral mesh models in a reference posture. As for the link structure model, the local coordinate system related to each link consists of the joint rotation center and the axes of joint rotation, which can be estimated based on the trajectories of optimal markers on the relative skin surface region of the subject obtained from the motion capture system. The skin surface model is defined as a three-dimensional triangular mesh, obtained by deforming a template mesh so as to fit the landmark vertices to the relative marker positions obtained motion capture system. In this process, anatomical dimensions for the subject, manually measured by a caliper, are also used as the deformation constraints.

Stretchable Strain Sensor With Anisotropy and Application for Joint Angle Measurement

Flexible and stretchable strain sensors are expected to significantly contribute to new technologies and be applied in various applications, including human interfaces, smart clothes, and robotic skin. Hence, we have proposed a flexible film-shaped strain sensor that is composed of three elastomer films and two carbon-nanotube electrodes. It is thin, lightweight, and has low elasticity. Strain measurements taken by the sensor are based on changes in capacitance, which is proportional to the square of the area of the sensors sensing part. Consequently, the capacitance of the strain sensor does not show the direction of the strain. As some applications require the measurement of strain in a fixed direction, this paper proposes an anisotropic strain sensor. This anisotropic strain sensor decreases the effect of the strain in the fixed direction to less than 10%. The model of the anisotropic strain sensor and experimental results show that its capacitance is proportional to the square of the length of the sensing part in the stretch direction. To check the anisotropic strain sensors practicality, it is applied to estimate the angle of a wrist joint. The results show that the anisotropy decreases the root-mean-square error of the estimated angle to less than 3°.

Finger Shell: Predicting Finger Pad Deformation under Line Loading

In this paper we introduce a new model of the mechanics of a finger pad that is efficient to simulate. The model simplifies the finger pad mechanics by assuming it to be a thin shell enclosing fluid-like material. Unlike similar approaches in the literature, we incorporate the bending stiffness of the skin and a subject-specific geometric model into the simulation. Thanks to these two features, our model can predict the surface deflection of the whole finger pad with the error of 0.2 to 0.4 mm with reasonable computational cost.