Metalens mounted on a resonant tunneling diode for collimated and directed terahertz waves.

Refraction in materials is a fundamental phenomenon in optics and is a factor in the manipulation of light, such as wavefront shaping and beam control. However, conventional optical lenses incorporated in numerous optical sources are made of naturally occurring materials, and material properties predetermine the lens performance. For the development of terahertz flat optics, we experimentally demonstrate a gradient-refractive-index (GRIN) collimating metalens made of our original reflectionless metasurface with an extremely high refractive index, above 10 at 0.312 THz. The planar collimating metalens converts wide-angle radiation from a resonant tunneling diode (RTD) to a collimated plane wave and enhances the directivity of a single RTD 4.2 times. We also demonstrate directional angle control of terahertz waves by moving the metalens in parallel with the incoming wave. The metalens can be simply integrated with a variety of terahertz continuous-wave (CW) sources for 6G (beyond 5G) wireless communications and imaging in future advanced applications. Flat optics based on high refractive index metasurfaces rather than naturally occurring materials can offer an accessible platform for optical devices with unprecedented functionalities.

Terahertz beam focusing through designed oblique metal-slit array.

Manipulation of propagating beams is essential in applications, and the potentially arising phenomena offer attractive optical components. However, the design of optical components using only naturally occurring materials has approached physical limits, and artificial materials such as metamaterials and metasurfaces are a way forward to open the door to sophisticated optical components. This paper shows manipulation of terahertz beams through designed oblique metal-slit arrays where a common metal-slit array does not perform as a lens. The oblique metal-slit array has a refractive index determined as a function of a steep angle. The lens consists of multiple metal plates with a designed oblique angle, and a convex output structure produces a focusing effect. We also suggest that the Brewster phenomenon in the lens can simply enhance the electric field intensity at the focal point. The Brewster condition of the lens is correlated with a jagged edged face on the input side with an appropriate metal-slit spacing and thickness. The phenomenon would be applicable to numerous promising components and applications such as gain-enhancement optical components and perfect impedance-matching polarizers.

Epsilon-near-zero three-dimensional metamaterial for manipulation of terahertz beams.

Metamaterials offer the potential of unprecedented refractive indices and evolution into metadevices for the manipulation of electromagnetic waves. However, the potential of the epsilon-near-zero (ENZ) concept has not been fully demonstrated in the terahertz waveband. Most conventional ENZ lenses have a uniform distribution of refractive indices in spite of their three-dimensional structure. Here, inspired by the ENZ concept, we demonstrate the two-dimensional distribution of a three-dimensional ENZ lens realized by circular openings of varying diameters on metal plates and apply it to a metal-slit array lens with gradient indices of 0

Robot-Assisted Eccentric Contraction Training of the Tibialis Anterior Muscle Based on Position and Force Sensing.

The purpose of this study was to determine the clinical effects of a training robot that induced eccentric tibialis anterior muscle contraction by controlling the strength and speed. The speed and the strength are controlled simultaneously by introducing robot training with two different feedbacks: velocity feedback in the robot controller and force bio-feedback based on force visualization. By performing quantitative eccentric contraction training, it is expected that the fall risk reduces owing to the improved muscle function. Evaluation of 11 elderly participants with months training period was conducted through a cross-over comparison test. The results of timed up and go (TUG) tests and 5 m walking tests were compared. The intergroup comparison was done using the Kruskal-Wallis test. The results of cross-over test indicated no significant difference between the 5-m walking time measured after the training and control phases. However, there was a trend toward improvement, and a significant difference was observed between the training and control phases in all subjects.

Negative refractive index metamaterial with high transmission, low reflection, and low loss in the terahertz waveband.

The refractive index is a basic parameter of materials which it is essential to know for the manipulation of electromagnetic waves. However, there are no naturally occurring materials with negative refractive indices, and high-performance materials with negative refractive indices and low losses are demanded in the terahertz waveband. In this paper, measurements by terahertz time-domain spectroscopy (THz-TDS) demonstrate a metamaterial with a negative refractive index n of -4.2 + j0.17, high transmitted power of 81.5%, low reflected power of 4.3%, and a high figure of merit (FOM = |Re(n)/Im(n)|) of 24.2 at 0.42 THz. The terahertz metamaterial with these unprecedented properties can provide various attractive terahertz applications such as superlenses with resolutions beyond the diffraction limit in terahertz continuous wave imaging.

Linear Logistic Regression for Estimation of Lower Limb Muscle Activations.

This paper addresses a technique to estimate the muscle activity from the movement data. Statistical models, such as linear regression (LR) models and artificial neural networks (ANNs), are good candidate estimation techniques. Although an ANN has a high estimation capability, it is frequently in the clinical application that a very small amount of data leads to performance deterioration. Conversely, an LR model needs fewer data, while its generalization performance is limited. In this paper, therefore, a muscle activity estimation method is proposed that uses a linear logistic regression model to improve the generalization performance. The proposed method was compared with an LR model and an ANN in verification experiments with several different conditions. The results suggest that the proposed method has a higher generalization performance than the conventional methods.

Inverse estimation of multiple muscle activations based on linear logistic regression.

This study deals with a technology to estimate the muscle activity from the movement data using a statistical model. A linear regression (LR) model and artificial neural networks (ANN) have been known as statistical models for such use. Although ANN has a high estimation capability, it is often in the clinical application that the lack of data amount leads to performance deterioration. On the other hand, the LR model has a limitation in generalization performance. We therefore propose a muscle activity estimation method to improve the generalization performance through the use of linear logistic regression model. The proposed method was compared with the LR model and ANN in the verification experiment with 7 participants. As a result, the proposed method showed better generalization performance than the conventional methods in various tasks.