Quantification and transmission of texture information is necessary in situations such as nursing care robots, where complex human-like movements are expected, or in telemedicine, where precise maneuvering from a remote location is required. Although various studies have been conducted to quantify the texture of objects, in order for a robot to detect the texture of unpredictable objects in real time, the robot must be small in size in addition to having the ability to detect the texture. In this study, we used an ultra-compact MEMS tactile sensor with a fingerprint-like concavo-convex structure in the contact area for texture detection, and evaluated the response when tracing the concavo-convex surface and the change in response depending on whether the sensor surface is concavo-convex or not and the structural period of the object. As a result, it was found that by introducing a concavo-convex structure to the contact area, it is possible to obtain a high intensity response in line with the surface concavity and convexity of the target.

In this study, we designed and fabricated a sensor integrating a heater and a resistance temperature detector for temperature detection and a photoresistor for light detection on a single chip, aiming at the combined measurement of tactile sensation, cold-warm sensation and color of a product. As a result, we confirmed the differences in thermal conductivity and optical transmittance. We also confirmed the difference in hardness using a tactile sensor.

This research includes investigation, prototyping, and evaluation of MEMS piezoelectric vibration energy harvesters from falling droplets. The devices have a simple structure, consisting of a 10×5×0.02 mm³ Si cantilever with 10 µm thick PZT thin films. The cantilever was coated with hydrophobic resin for electrical insulation and high Q factor. The collision impact of the droplets vibrates the cantilever and PZT generates the electric power. In this paper, two types of the device, with and without a proof mass at the free end of the cantilever, were fabricated and evaluated. The experiments showed that the device with mass generates maximum voltage of 5.7 V and the total energy of 313 nJ from one droplet of 15 µJ.

To obtain a large power output by using MEMS vibratory energy harvesters, multiple devices can be used with connected together and their output synchronized. In this study, a butterfly-shaped harvester composed of two cantilever harvesters with weak mechanical coupling is proposed. For the fabricated test device, synchronized vibration of the two cantilevers as both wings of butterfly shape is successfully observed and the power output was doubled in the experiments. The mechanical coupling between the cantilevers is discussed by using equivalent circuit model. Based on the model, the devices with an additional mass to enhance the synchronization were fabricated and evaluated. The experimental results agree well with the calculation.

The authors have studied a tactile sensor that simultaneously detects strain and temperature. In this paper, we used a Cr-N alloy thin film with high strain sensitivity and low temperature sensitivity and Fe-Pd with high temperature sensitivity and low strain sensitivity as strain and temperature sensors for a composite tactile sensor. We prototyped the composite tactile sensor, conducted simultaneous application tests of strain (load) and temperature, and discussed correction methods to improve detection accuracy. The fabricated composite tactile sensor enabled simultaneous measurement of strain (load) and temperature. We also confirmed that it is possible to compensate for each other in real time through simple calculations, without the need for a special compensation circuit by using two thin films with the above characteristics.

In our society, where the number of people suffering from heat-related illnesses is increasing due to global warming, it is expected to develop a technology to conveniently measure core body temperature under active conditions, which is vital biological information for predicting heat-related illnesses. Measuring methods of core body temperature from thermal flow on the skin surface noninvasively have been reported so far, but the technical problem to be solved is that it cannot cope with changes in ambient temperature and air flow, which easily occur in daily life, and causes large measurement errors. This study aims to develop a new core body temperature measurement method that can respond to environmental changes based on a unique sensor structure and core temperature calculation model. The proposed method has two features. One has a new structure to eliminate the influence of environmental changes on the measurement data. The other is the development of a new calculation model of core body temperature that takes into account the heat capacity of the skin, and features a reduction in measurement errors during unsteady conditions. Here, the effect of the structure and calculation model on the estimation error is analyzed multilaterally through numerical simulation, and the effectiveness of the proposed method is shown by the fact that it can estimate core body temperature with high accuracy over a wide range of temperature and wind speed compared with the conventional method.