This study proposes a user's intuitive intention-based control system for mobile robot platforms. As an application of the control scheme, we focused on a robot that transports patients in medical facilities. However, since most of the people who operate the patient transfer robot (PTR) are not robotics experts, an intuitive control method is needed to enable easy operation of the robot system. Also minimizing the discomfort experienced by the patient in the process of transferring the patient through the patient transfer robot is another important issue to consider. Therefore, the main contributions of this are developing an intuitive user interface and proposing a sway reduction control scheme. To accomplish the first issue, the intuitive control is implemented by proposing a robot control interface, where four force-sensing resistor (FSR) sensors are installed on a robot's handle (where a user holds a robot). Through this, the robot can be easily moved with only a simple and intuitive operation of the user. Therefore forward, backward, left movement, right movement, left turn, and right turn operation can be controlled through the intuitive movement of the user input through the developed user interface. Additionally, in order to satisfy the second requirement, the patient's sway reduction strategy is suggested by applying fuzzy logic-based control command generation method to the user intention. Through this method, the sway that occurs during the movement of the robot is reduced. In this study, the mecanum wheel was applied to the driving platform of the patient transfer robot to enable omnidirectional movement. The performance of the proposed control method is verified through simulations and experiments. Simulation and experimental results confirm that the proposed method reduced the acceleration and jerk root mean square values of the robot compared to a comparison method.

This paper presents an algorithm to control a robotic prosthetic hand by applying deep learning (DL) to select a grasping pose and a grasping time from 2D images and 3D point clouds. This algorithm consists of four steps: 1) Acquisition of 2D images and 3D point clouds of objects; 2) Object recognition in the 2D images; 3) Grasping pose selection; 4) Choice of a grasping time and control of the prosthetic hand. The grasping pose selection is necessary when the algorithm detects many objects in the same frame, and must decide which pose of the prosthetic hand should use. The pose was chosen considering the object that was to the prosthesis. The grasping time was determined by the operating point when approaching the selected target after selecting the grasping pose; this choice uses an empirically-determined distance threshold. The proposed method achieved 89% accuracy of the grasping the intended object. The failures occurred because of slight inaccuracy in object localization, occlusion of target objects, and the inability of DL object detection. Work to solve these shortcomings is ongoing. This algorithm will help to improve the convenience of the user of a prosthetic hand.

We developed an integrated PCR system that performs automated sample preparation and fast polymerase chain reaction (PCR) for application in point-of care (POC) testing. This system is assembled from inexpensive 3D-printing parts, off-the-shelf electronics and motors. Molecular detection requires a series of procedures including sample preparation, amplification, and fluorescence intensity analysis. The system can perform automated DNA sample preparation (extraction, separation and purification) in ≤5 min. The variance of the automated sample preparation was clearly lower than that achieved using manual DNA extraction. Fast thermal ramp cycles were generated by a customized thermocycler designed to automatically transport samples between heating and cooling blocks. Despite the large sample volume (50 μL), rapid two-step PCR amplification completed 40 cycles in ≤13.8 min. Variations in fluorescence intensity were measured by analyzing fluorescence images. As proof of concept of this system, we demonstrated the rapid DNA detection of pathogenic bacteria. We also compared the sensitivity of this system with that of a commercial device during the automated extraction and fast PCR of Salmonella bacteria.

Typically, the actual volume of the residual limb changes over time. This causes the prosthesis to not fit, and then pain and skin disease. In this study, a prosthetic socket was developed to compensate for the volume change of the residual limb. Using an inflatable air bladder, the proposed socket monitors the pressure in the socket and keeps the pressure distribution uniform and constant while walking. The socket has three air bladders on anterior and posterior tibia areas, a latching type 3-way pneumatic valve and a portable control device. In the paper, the mechanical properties of the air bladder were investigated, and the electromagnetic analysis was performed to design the pneumatic valve. The controller is based on a hysteresis control algorithm with a closed loop, which keeps the pressure in the socket close to the initial set point over a long period of time. In experiments, the proposed prosthesis was tested through the gait simulator that can imitate a human’s gait cycle. The active volume compensation of the socket was successfully verified during repetitive gait cycle using the weight loads of 50, 70, and 90 kg and the residual limb model with a variety of volumes. It was confirmed that the pressure of the residual limb recovered to the initial state through the active control. The pressure inside the socket had a steady state error of less than 0.75% even if the volume of the residual limb was changed from −7% to +7%.

Herein, lipid-coated polyaniline (LiPAni) nanoparticles were fabricated to monitor the redox state of cancer cells. To confirm the characteristics of LiPAni, we firstly analyzed the size and chemical structures of the LiPAni nanoparticles. The absorbance properties of the LiPAni nanoparticles were observed to vary with the pH conditions. Furthermore, cell viability tests conducted with breast cancer cell lines showed that the cell viability of the cells with LiPAni nanoparticles was dramatically increased compared to those with the Tween80-coated polyaniline nanoparticles (TPAni) as a control. Subsequently, the colors of the LiPAni nanoparticles were observed and analyzed using spectroscopic methods. Finally, in order to investigate the more accurate sensing of the redox state using the color changes of the LiPAni nanoparticles with cancer cell lines, dark field microscopic images and scattering spectra were recorded at the single nanoparticle scale. For the TPAni nanoparticles, there was only a change in brightness and no change in color, but for the LiPAni nanoparticles, there was a change of color from yellow to pink in the dark field images.

A new button-shaped electrical device was developed for a smart fabric. This electric button can be sewn anywhere on the garment, similar to a traditional button fastener. t not only performs a decorative function but also makes the fabric suitable for use in Internet of Things (IoT) applications. It has metallic through-holes such that it can be fastened onto a fabric by conductive sewing threads. When threaded through metallic holes, the button can communicate with the external device by transmitting and receiving data. In addition, it adds specific functions by stacking a detachable application layer on the base layer. It is robust to frequent washing, and thus has excellent repeatability for use as an IoT device. The feasibility of the electric button was successfully demonstrated by its ability to identify the physical activities of walking and running, monitoring ambient temperature, and turning on LED lights.

We developed a sensitive and reliable thermal micro-flow sensor (T mu FS) to measure extremely low flow rates for a drug infusion system. The T mu FS exploits a calorimetric principle. Various temperature differences upstream and downstream of a heated area were monitored by three temperature sensors to enable measurement of both cooling and heating effects at the multiple temperature-sensing areas. The flow rate was measured by subtraction or summation of the temperature differences between selected locations upstream and downstream. The temperature differences between heat loss and diffusion increased sensitivity of flow rate detection in range of 0-100 mL/h. The T mu FS takes non-invasive and non-intrusive measurements by monitoring thermal variations on the outer surface of a silicone IV tube. The T mu FS could detect flow rates as low as similar to 0.1 mL/h, with uncertainty <5%. The micro-flow sensor was accurate at a range of flow rates, initial liquid temperature, and tube inner diameters. In addition, temperatures variations in the T mu FS for flow rates agreed with numerical simulation. (C) 2020 Elsevier B.V. All rights reserved.

Polyaniline nanoskein (PANS), which have polyaniline nanofibers, is developed. PANS is formulated via sequential extracting, heating, and swelling processes. The compositions of PANS have been analyzed using X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, and Brunauer-Emmett-Teller analysis, and the results of which indicate that PANS is composed of solely organic materials. Moreover, PANS have been shown convertible absorbance characteristics according to surrounding acidic environments, and using these characteristics, the possibility of PANS for sensing of surrounding redox states changes is presented.

Robotic prosthetic hands are a device that helps to improve the quality of life for patients without hands. Recently, robotic prosthetic hands can perform various grasping patterns because of improvement of bioengineering and robotics. The research that automatically selects the appropriate operation according to the situation is important. Many previous studies have used EMG signals. However, EMG signals are difficult to generalize because EMG signals vary depending on the position of the muscle. In this study, we developed a system for controlling robotic prosthetic hands using images and deep learning to facilitate generalization. We also proposed a method for selecting a grasping target to be held in the image. These results will help to improve the quality of life of the robotic prosthetic hand user.

Fully automated system for sample preparation in molecular diagnostics was developed. The small cartridge with multiple chambers and a rotating valve was designed for automated processes such as extraction, separation and purifications during the DNA sample preparation. The automated processes such as injection, mixing, capturing and valve on/off motions were controlled by an affordable, motorized control system. We demonstrated the automated DNA extraction of pathogenic bacteria using this system. The deviations in the purity and real-time polymerase chain reaction (PCR) detection of the automated DNA extraction samples were clearly decreased. The device provided rapid, reliable, and reproducible sample preparation in comparison with manual DNA extraction. This automated platform can be utilized in emergent point-of-care testing of infectious disease and foodborne bacteria.

The autonomous emergency braking system is one of advanced driving assist systems. It is an advanced safety function designed to prevent collision with a forward vehicle or a pedestrian in the event of driver’s carelessness or a sudden accident ahead. Because the AEB stops the vehicle with a maximum deceleration command at the last possible time to brake so that collision avoidance is possible, it can prevent a collision with a preceding vehicle. However, there are risks of a secondary collision with a trailing vehicle and injury to a passenger due to sharp deceleration. In addition, sudden braking control can present a driving feeling gap to the driver. These problems must be solved because they can amplify a user"s rejection of automatic emergency braking (AEB) and negatively affect the acceptability of this technology. In this study, the driver"s braking propensity is derived by means of deep learning and it is applied to a customized AEB system to prevent secondary accidents caused by sudden braking and to improve user acceptance. In order to derive a driver"s braking behavior, normal driving data and stationary target based braking test data are collected. Utilizing a deep neural network, the driver’s braking profile during ordinary driving and a sudden stop are extracted. The correlation between the two extracted driver’s braking behaviors is analyzed. This provides the means to derive sudden braking behavior as a function of driving speed, leading to customized AEB parameters.

Optimal design of transmission gears is important to ensure product durability and reliability. This study measured a multi-purpose cultivator during a rotary ditching operation and analyzed the strength of the power take off (PTO) gear-train for the cultivator using analysis software (KISSsoft, KISSsoft AG—A Gleason Company, Bubikon, Switzerland) based on ISO 6336 standards and a modified Miner’s rule. A load measurement system was installed on the cultivator to measure the load on the PTO shaft. To measure the load on the PTO shaft, the load measuring system consisting of a data acquisition board (NI USB-6212, National Instruments, Austin, TX, USA) and a torque sensor was installed on the cultivator. Rotary ditching operations were conducted at two ground speeds and two PTO rotational speeds on a field with the same soil conditions. The measured load data were constructed using the rainflow-counting algorithm and the Smith-Watson-Topper equation. When the ground speed or PTO rotational speed increased, the average and maximum PTO torque increased significantly. The average measured torque ratio to rated torque of the PTO input shaft (19.6 Nm) was in the range of 50.1–105.9%. The simulation results using the actual measurement load indicated that the strength of the PTO gear-train tended to decrease with higher transmission gear stage and lower PTO gear stage except for the G2 and G3 gears. The simulation results of the safety factor for contact stress were lower than the minimum safety factor of ‘1.0’ at the T2P1 gear stage (G4 and G2). The simulation results of the fatigue life analysis showed fatigue life of less than service life (1000 h) at T2P2 (G2) and T2P1 (G2, G3, and G4). The simulation results indicate that there is a possibility of gear failure before service life at the T2P1 (G2, G3, and G4) and T2P2 (G2). It is known that the weak parts (G2, G3, and G4) should be the focus of design optimization through gear strength simulation to meet upward of a 1.0 safety factor and service life.

A body pressure relief system was newly developed with optical pressure sensors for pressure ulcer prevention. Unlike a conventional alternating pressure air mattress (APAM), this system automatically regulates air flow into a body supporting mattress with adaptive inflation (or deflation) duration in response to the pressure level in order to reduce skin stress due to prolonged high pressures. The system continuously quantifies the body pressure distribution using time-of-flight (ToF) optical sensors. The proposed pressure sensor, a ToF optical sensor in the air-filled cell, measures changes in surface height of mattress when pressed under body weight, thereby indirectly indicating the interface pressure. Non-contact measurement of optical sensor usually improves the durability and repeatability of the system. The pressure sensor was successfully identified the 4 different-predefined postures, and quantitatively measured the body pressure distribution of them. Duty cycle of switches in solenoid valves was adjusted to 0–50% for pressure relief, which shows that the interface pressure was lower than 32 mmHg for pressure ulcer prevention.