Effect of linearly polarized microwaves on nanomorphology of calcium carbonate mineralization using peptides.

Microwaves are used for diverse applications such as mobile phones, ovens, and therapy devices. However, there are few reports on the effects of microwaves on diseases other than cancer, and on physiological processes. Here, we focused on CaCO3 mineralization as a model of biomineralization and attempted to elucidate the effect of microwaves on CaCO3 mineralization using peptides. We conducted AFM, ζ potential, HPLC, ICP-AES, and relative permittivity measurements. Our findings show that microwaves alter the nanomorphology of the CaCO3 precipitate, from sphere-like particles to string-like structures. Furthermore, microwaves have little effect on the mineralization when the mineralization ability of a peptide is high, but a large effect when the precipitation ability is low. Our findings may be applicable to not only the treatment of teeth and bones but also the development of organic-inorganic nanobiomaterials. This methodology can be expanded to other molecular/atomic reactions under various microwave conditions to alter reaction activity parameters.

Change Detection of Sleeping Conditions based on Multipoint Ambient Sensing of Comforter on Bed.

This paper describes a method for the detection of changes in sleeping conditions using multipoint ambient sensing for safety and amenity in the sleep environment. This method continuously detects changes during sleep, such as the movements of the person and bedding based on the measurement of acceleration, temperature and humidity of the comforter. Through the measurement of these ambient conditions, this system improves sleep quality and prevents accidents, such as falling off the bed. In this study, a basic system using internet of things (IoT) devices is constructed, and performance verification is conducted. The experimental results show the feasibility of the proposed method.

Development of health monitoring system based on three-dimensional imaging using bio-signals and motion data.

The purpose of this study is to develop a health monitoring system. This system represents human health condition and human motion simultaneously. This system obtains motion data by optical motion capture system. Electromyogram and electrocardiogram are used for health condition estimation. These are measured synchronously with motion data. Two experiments were performed to evaluate our system. In these experiments, muscle activity, motion of the heart and the autonomic nervous balance were represented as health conditions. This system contributes intuitive recognitions of health condition and high accurate estimation of health conditions.

Estimation of bio-signal based on human motion for integrated visualization of daily-life.

This paper describes a method for the estimation of bio-signals based on human motion in daily life for an integrated visualization system. The recent advancement of computers and measurement technology has facilitated the integrated visualization of bio-signals and human motion data. It is desirable to obtain a method to understand the activities of muscles based on human motion data and evaluate the change in physiological parameters according to human motion for visualization applications. We suppose that human motion is generated by the activities of muscles reflected from the brain to bio-signals such as electromyograms. This paper introduces a method for the estimation of bio-signals based on neural networks. This method can estimate the other physiological parameters based on the same procedure. The experimental results show the feasibility of the proposed method.