In this paper, a multi-functional pressure sheet sensor is proposed for the unconstrained vital signs such as respiration, pulse and body posture measurements. The sheet sensor is matrix structure which consists of piezoelectric and conductive films with the soft dielectric material. The pulse is measured with the piezoelectric film. In addition, the capacitance distribution is measured with the surface electrodes of piezoelectric films and conductive films. The body posture and the respiration are respectively measured with the capacitance distribution and its change. As the experiment, the simultaneous measurement of the respiration, pulse and body posture on the bed was demonstrated by the sheet sensor, and the possibility of the vital signs and body posture measurements was presented.

In recent years, with the spread of electric vehicles, improvement in the performance of lithium ion batteries has been required. Evaluation of the active material is important because the performance of the lithium ion battery is affected by the movement of lithium ions at the electrode active material-electrolyte interface. In this study, we fabricated a lithium ion battery with the sensing plate, which is a potential sensor, attached to the positive electrode, and evaluated lithium ion battery with a Terahertz Chemical Microscope. As a result, we succeeded in measuring the potential distribution of the positive electrode during charging and discharging, and the local impedance.

In this paper, we report a development of quartz crystal complex capacitive sensor with microelectrode array for local detection of liquid sample. This sensor is composed of the sensing capacitor (SC) with microelectrode array and quartz crystal resonator (QCR). It is a contactless capacitive sensor using out-of-plane electric field of a planer sensing capacitor. We succeeded in confining the electric field by placing microelectrode array on the SC and improving the spatial resolution of the sensor. This sensor enables local capacitive detection of target materials. This sensor is expected to be applied to the detection system of µ-TAS.

To digitalize handwork that remains at manufacturing sites, we developed a glove with built-in sensors that capture fingertip pressure and work sounds. To create an identification model with small amounts of training data, we developed a handwork identification model based on machine learning, in which a hidden Malkov model (HMM) extracts features from time-series information of sensor data and a support vector machine (SVM) identifies the type of handwork. The developed gloves and model identify specific handwork every 0.01 seconds. We experimentally confirmed that our proposed model can distinguish two typical types of handwork—connector insertion and screw tightening with a pistol grip electric screwdriver—with 82% accuracy from only 20 seconds of training data for each. This technology can be applied to recording handwork evidence and automation of incorrect work detection.

A potassium-ion electret, which is a key element of vibration-powered microelectromechanical generators, is a material that permanently stores negative charge. However, the charge storing mechanism of a potassium-ion electret is still unclear. In this study, we theoretically study the atomic and electronic structures of amorphous SiO₂ with and without potassium atoms using first-principles molecular-dynamics calculations. As a result of calculations, we confirmed the existence of a fivefold-coordinated Si atom with five Si-O bonds as a characteristic local structure in a-SiO₂ with potassium atoms, which is negatively charged. This result indicates that the fivefold-coordinated Si structure is the physical origin of the negative charge observed in potassium-ion electret. Furthermore, we show the guidelines for the experimental observation of the fivefold-coordinated structure and the fabrication of high-reliability potassium-ion electret.