Electronics and Communications in Japan最新文献

In recent years, various user interfaces have been developed to meet the diverse needs of physically disabled persons. In this paper, we developed a method to identify gazing and facial movements based on gaze time and eye/face information and developed an electric wheelchair that can be operated with the user's natural gazing and facial movements. This intention estimation model is composed of 1DCNN and LSTM layers. First, 1DCNN is used to extract features from gaze and face information, and then the extracted features are input to LSTM to estimate the user's intentions regarding movement. The evaluation experiments suggest that the combination of gaze and face information improves the estimation accuracy and contributes to the classification. Furthermore, it was confirmed that adding a convolutional filter layer to the LSTM layer improved the accuracy.

Low molecular weight silicones were ejected from silicone rubber target irradiated by a 193 nm ArF excimer laser through the photo-desorption. The ejected silicones were successfully deposited on a fused silica glass substrate in air. An approximately 0.3 mm of the target-substrate distance was required for the deposition. The deposited silicones became a thin film, showing an interference color when the ArF excimer laser was irradiated for a long time. Chemical bonding state of the formed thin films was analyzed by the Fourier transform infrared spectroscopy. The thin films were slightly different from the original silicone rubber structure, still it was composed of Si-O-Si bonds and Si-CH₃ bonds. Also, OH bonds were clearly produced in the silicone thin films. As a result, contact angle of water on the silicone thin films was measured to be approximately 20 degrees, indicating a hydrophilic property.

We proposed elemental technique for reducing power supply voltage and circuit scale for CMOS exponentiation conversion IC utilizing weak inversion operation to mount it on microcomputer chip. This IC implements to change the power exponent to any value by amplifying with adjusting gain after converting signal logarithmically, and finally converting it exponentially. We showed that the circuit scale can be reduced to several tenth times in order to generate a weak inversion current by cascading multiple stages of current-dividing current mirror circuits. Due to this current mirror circuit, circuit scale was reduced to 34.4%. We also proposed an exponential converting circuit that can halve the input voltage by using one pair of weak inversion MOSFETs. However, the proposed control method of the exponential value by utilizing the substrate effect was found to have about 8% of narrow control range. Although measured result shows that this IC does exponentiation conversion, power exponent value was 56% smaller than simulation result.

Establishment of real-time monitoring technique for blood viscosity during extracorporeal circulation treatment is needed. We have demonstrated that red blood cell (RBC, hereafter) aggregation degree, which highly correlates with the blood viscosity, can be estimated by the ultrasound spectroscopic observation of the RBC and the defining of the peak frequency by the Fast Fourier Transform process. In this study, the peak frequency was measured to investigate the aggregation degree of RBC flowing in a simple heart-lung machine. In addition, to disassemble the RBC aggregations that might cause the clogging of the circuit, a disassemble technique of the RBC aggregations using a focused 5 MHz ultrasonic transducer was also proposed. As the first step of this study, the disassembling of the RBC aggregations was carried out under the still condition and its effect was confirmed by the peak frequency method.

Here, we report a novel biosensing system using a finger-powered microfluidic device, which is suitable for daily self-testing of uric acid in saliva. To realize the rapid determination of salivary uric acid, the biosensing system measures directly from the paper-based saliva sampling device. The microfluidic device has the diaphragm pump, the reagent reservoir, and the reaction cell in which the electrochemical uric acid biosensor is embedded. Once the microfluidic chip has been folded, the finger-powered microfluidic device prepares the reagent containing the saliva, which is ready to measure. A wireless potentiostat for electrochemical measurement of uric acid with the biosensor was also developed. Combining these elements together, the whole process from saliva sampling to determination was completed in less than a minute (Sensitivity: 0.03 nA/μM). The measurement results were also consistent with that measured using a commercially available uric acid determination kit. Hence, our method is expected to have the potential to enhance the use of biochemical information in the field of healthcare IoT.

In this study, a brain network was created using graph theoretical analysis based on electroencephalography (EEG) data. The purpose of the study was to investigate the functional connectivity of the brain in different states of anxiety. Seventeen adults with anxiety (A-G), and 13 adults without anxiety (AF-G) were examined. They were given three different stimulations: resting, pleasant, and unpleasant. EEG was measured immediately after the stimulation. The EEG was analyzed by Fast Fourier Transform (FFT), coherence analysis, and graph theory. The results of FFT and coherence analysis showed that the anxiety group (A-G) had higher power spectra and coherence values than those for the anxiety-free group (AF-G) in all sessions. The results of graph theory analysis showed that the clustering coefficient and small-worldness in A-G were lower than those in AF-G, although the characteristic path length in A-G was higher than that in AF-G. This study shows that the brain of A-G has smaller clusters and longer paths to compare with those of AF-G. These events suggest that the brain of A-G would have an inefficient network structure to transmit emotional information.

HF and LF/HF, which are parameters of the frequency domain of the electrocardiogram R-R interval time series, are general index of the autonomic nervous activity balance. Most wristwatch-type heart-rate monitors measure heart rate from sphygmograph and interpolate missing data. These are the causes of reducing the calculation accuracy of LF and HF. The purpose of this study is to propose a method for estimating LF and HF calculated from the ECG R-R interval time series from the heart-rate time series at 1-s intervals measured by a wristwatch-type heart-rate monitor. Six hundred and seventy data-set with a length of 120 s measured simultaneously with an electrocardiogram and a wristwatch-type heart-rate monitor during standing cooking operation, up-right standing, watching slide show in standing posture, and resting supine position were used. Seventy percent dataset were used for modeling, and remaining 30% were used for evaluating model. As a result, the coefficient of determination of LF and HF were 0.441 and 0.467, respectively in the one-variable polynomial regression model. The coefficient of determination of LF and HF were 0.557 and 0.644, respectively in the multivariable regression model, based on Random Forest and time domain indices.

The purpose of this study is to develop a line-of-sight input interface using the eye-glance input method, which uses a glance eye movement and method of estimating the eye-control movement by analyzing the image of the area near the eye-ball. The motion was discriminated by taking an image using the built-in camera of a smartphone to rapidly look at the four corners of the smartphone and calculate the moving distance of the eyeball, which was divided into horizontal and vertical components using the optical flow function in Open CV library. In the experiment, we obtained data by asking the subjects to look at the reciprocate of quick gaze movements at each of the four corners and the center of the screen. As a result of data analysis, characteristics of waveforms were obtained for the movements looking at the four corners, and we could determine which of the four corners the users were looking at. Furthermore, by distinguishing between camera shake and line-of-sight movement using the variance value, the discrimination rate was 90% or more even when held in the hand. It was shown that the Eye Glance movement can be measured with a smartphone as well as a PC.

In this paper, consecutive meals planning is formulated as a multiset iteration permutation problem that determines the optimal meals plan on a period consisting of consecutive days. In this problem, a meal is characterized by some characteristics such as food style, ingredient, cooking method, and so on. The evaluation function is defined by use of information entropy for measuring the appearance order of meal's characteristics on the meals plan. For optimizing this problem, Genetic Algorithms (GAs) with escape from stagnation of search are proposed. It is empirically shown that the proposed GAs with escape operation work better than the conventional permutation GA without escape operation for small and large size optimization problems.

In recent years, the demand for highly nutritious and functional vegetables has been increasing in the agricultural sector. In order to cultivate highly functional vegetables, it is necessary to adjust the nutrients in the soil, such as potassium ions, to an optimal state. Therefore, there is a need for a sensor that can measure soil ion concentration in real time in the field. In this report, we aim to develop an ion concentration sensor using Nuclear Magnetic Resonance (NMR). Since the sensor observes atomic specific behavior, it has the potential to measure the concentration of each ion species in soil where multiple ions exist. In this study, we aim to realize compact NMR and to establish a method for NMR measurement of water ahead of ion measurement. Using an NMR measurement system of our own design, we measured water and air. As a result, NMR signal spectra were obtained only when measuring water under resonance conditions, and resonance frequency of hydrogen atoms were successfully measured. We have established an NMR signal measurement method for measuring ion concentrations using a small NMR sensor that can be installed in the agriculture.