PPG imaging is a photoplethysmography by digital image processing. In many cases, a facial video image of web-camera quality is processed to obtain a photoplethysmographic signal. In this study, PPG imaging with Xilinx窶冱 Zynq UltraScale+MPSoC is attempted to develop a small and power saved IoT device for physiological measurement in the field. The UltraScale+MPSoC is a System-on-a-chip (SoC) having both programmable logic cells as FPGA and an arm-based processor, then this SoC is suitable for developing real-time applications. In this study, a PPG imaging application has been developed with using Xilinx窶冱 Vitis Vision Library, then, real-time ROI selecting of the face and PPG detection by summation of ROI with almost 30 fps in real-time processing is achieved.

Atrial fibrillation (AF) is one of the arrhythmias that causes a stroke, and early detection is required. In many ECG inspections, irregular RR-intervals (RRI) are first detected. Therefore, rare AF with regular RRI could be overlooked. As the other features, an ECG waveform of AF has several small waves (f-wave) and the absence of P-waves. In this study, a novel AF detection method by identifying these two features with a convolutional neural network (CNN) is proposed. In preprocessing, the artifacts on the ECG waveform are removed by a bandpass filter. First, the R-waves are detected using a variable threshold. Next, the waveform in 0.4 s before each R-wave is extracted. Then the f-wave and P-wave are identified using CNN with the LeNet structure, and AF is detected. Evaluating the performance with untrained ECG waveforms of 10 subjects, the accuracy was 84.0%. This result indicates the feasibility of this method.

Appropriate pharmacological intervention in the setting of acute heart failure (AHF) presents unique challenges for each patient. Early identification of patients who will not respond to pharmacological therapy alone would be crucial in the clinician窶冱 decision to provide additional therapy such as mechanical support. This paper proposes the concept of drug determined reachability, the maximum range that multiple drug infusions can span cardiovascular parameters. Our approach models how multiple drug infusion affects key cardiovascular parameters, while considering dosage limitations, multi-dependencies of multiple drugs, and nonlinear interaction of drugs to the gradient of the Frank-Starling Curve. The simulation of drug determined reachability sheds light on the effectiveness or limitation of closed-loop therapeutic systems for acute heart failure treatment depending on each patient窶冱 pathophysiological scenario.

The human vein is an important passage for injection of medicine and peripheral intravenous catheters are the most used device for intravenous therapy in the hospital. However, premature removal of peripheral intravenous catheter happens frequently by mechanical complications such as phlebitis, occlusion, and infiltration which brings a great decrease in patient’s health-related quality of life. The failure is hard to prevent, as continuous monitoring of veins is difficult, and nurses should observe the status using ultrasonography periodically. To support the catheterized vein monitoring system, vein flow velocity estimation and vein location detection were done by using 8-electrodes impedance tomography for continuous monitoring. Both multi-frequency skin impedance analysis and photoplethysmography signal similarity were used and confirmed the validity by comparing with ultrasonography. This study confirmed there is significant correlation (ρ=0.74, p<0.05) between methods of velocity estimation and showed the possibility of monitoring the catheterized vein continuously and non-invasively.

In this study, we examine whether two positive psychological indicators, Flow Frequency, Coping, and one negative psychological indicator, Trait-Anxiety can be determined based on heart rate parameters. The experiment is conducted on 16 healthy subjects, and their heart rate is recorded using a Fitbit Charge 2 device. To acquire heart rate parameters, four cosinor-based variables such as cosinor 24-Hour periodic component, cosinor 12-Hour periodic component, cosinor periodic component amplitude, and cosinor autonomic switching rate are extracted from the original heart rate sequence during 24 hours by using the double cosinor method. We measure psychological indicators by employing dispositional questionnaires. The PCA results show a substantial correlation in Flow Frequency and Coping (R2>0.3, p<0.05 with a single principal component and R2>0.4, p<0.05 with multiple principal components). Trait-Anxiety demonstrates a negative correlation with physiological parameters. According to this finding, there is a positive correlation between positive psychological indicators and heart rate parameters.

Many systems have been developed to monitor the health and living conditions of older people living alone. We have developed a system that monitors the indoor life of older people living alone by monitoring their TV usage. We have been operating it for over 10 years. As the system requires regular maintenance and antivirus environment, it became difficult to continue the operation. Therefore, we redesigned a new system to reduce maintenance and to make the system smaller. The new system consisted of a microcomputer with LCD, four sensors, and a free database. The sensors detect TV usage, infrared remote-controller, room light/dark, and lightning fixture operation. The new system is essentially maintenance free and, the size of the device installed next to the TV is now about 20% of the size of the previous one. In a trial, the new system is working as well as the previous system.

In our laboratory, a mathematical model of the decision-making process was constructed and the individual differences of the process in gold trading were represented reasonably, and the learning process was indicated as the convergence of model parameters. However, the learning process in decision-making process has not been identified using a mathematical as far as authors know. Thus, in this research, the learning process was examined using the already constructed model which consist of proposal, integrator, and derivative elements and compared the individual differences in decision-making between in gold trading game and in forex trading game.According to the results, the learning process of all players were represented reasonably. Also, the individual differences in learning process were represented so clearly that the difference of difficulty in learning was grasped between in gold trading and forex trading.