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Wearable haptic displays can provide haptic information while allowing for free body movement. Among these haptic displays, pneumatic haptic displays have the advantages of flexibility and lightweight; however, they require bulky air tubes and a heavy air compressor. To solve this problem, we propose a wearable haptic display that uses a liquid-to-gas phase change actuator and a Peltier device as a way to reduce the size of the entire system. A low-boiling-point liquid is encapsulated in the flexible bladder of the actuator, and the vaporization of the liquid, which induces the inflation of the actuator, is controlled by the external Peltier device. In this study, we implemented a pressure sensor to monitor pressure inside the liquid-to-gas phase change actuator. The pressure measurement will contribute to controlling the generated normal force. First, we characterized the pressure response concerning the design of the liquid-to-gas phase change actuator. Next, we evaluated the output normal force of the haptic display and confirmed that the maximum output force reached a few newtons, which is a similar level to the off-the-shelf wearable haptic display devices. Finally, a sensory evaluation revealed that the experimental participants perceived the haptic stimulus to their fingertips provided by the proposed haptic display in a few seconds. According to the obtained results, the proposed haptic display can be applied to applications such as human interfaces to provide force, allowing for a response time of a few seconds.

In this study, we examined information leakage in photoplethysmogram (PPG)-based biometric authentication and assessed an attack against authentication based on the information leakage. Several approaches have been proposed to apply PPG to biometric authentication using a wearable device; however, there may be several attacks against PPG-based authentication. One of the attacks is a “presentation attack” (PA), which utilizes the information leakage originating from the various PPG measurement sites on a body. The PA records the victim’s PPG stealthily on non-genuine measurement sites and transmits it to the PPG sensor to break the authentication. We examined the information leakage and assessed the PA by evaluating feature values extracted from the PPG signals. We recorded the PPG signals of 12 participants on their fingertips and wrists. We compared the feature values extracted from the recorded PPG signals by computing the differences, correlation coefficients, and mutual information to examine the leakage of information required for the PPG-based authentication. We then assessed the feasibility of a PA based on existing PPG-based authentication algorithms and evaluated the contribution of each value to authentication and PA by computing the permutation importance of all feature values. The experimental results indicated that there might be information leakage and selection of feature values to reduce the feasibility of the PA up to 62.8 %.

In this study, we propose a countermeasure against a presentation attack on a photoplethysmogram (PPG)-based biometric authentication system. The countermeasure detects fake PPG signals by identifying PPG measurement sites on the body based on the difference between PPG waveforms recorded at genuine measurement and non-genuine sites without adding other sensing components. In an experiment, we computed the correlation coefficients as the similarity indices between PPG waveforms using two datasets, i.e., PPG signals recorded at multiple measurement sites on participants and mapped signals to generate fake signals for authentication. We then evaluated the proposed countermeasure using the feature values extracted from the PPG signals to identify the measurement sites on the body. The experimental results indicated that the identification of measurement sites as a countermeasure operated successfully for both PPG datasets, regardless of the presence or absence of waveform mapping, and exhibited an identification accuracy of more than 90 % regardless of the elapsed time.

Sagittal split ramus osteotomy is the most commonly performed for jaw deformity patients in oral and maxillofacial surgery (OMS). In recent years, virtual reality-based surgical training simulators have been developed for reducing the cost of simulated bone, however, effective assistance methods for improving surgical skills have not been well studied. Therefore, the purpose of this study is to develop a manipulation assistance method for surgical training simulator with haptic rendering. The surgical training simulator system is composed of three modules: pre-processing module, interactive surgical training module, and evaluation module. In this paper, we newly implement the pre-processing module for correct answer data generating method, interactive surgical training module for enable users to feel the unique reaction force including cortical bone and cancellous bone, and improve the evaluation module for correct answer data. In the evaluation experiments, 4 testees of surgeons and 4 testees of engineering students performed the surgical training for 1 jaw deformity patient. The training consisted of 3 sets of 5 repetitions. As the results, it was confirmed that our surgical training simulator has the ability to simulate actual surgery from the trials of surgeons. It was also confirmed that bone drilling technics of students had improved by repeating trials. These showed the usefulness of our surgical training simulator. Future work will include additional force assistance and graphic stereoscopy with head-mounted-display.

Bioelectrical impedance method is useful for evaluating tissue state such as muscle injury but there is a trade off between efficiency and robustness in detection of various local impedance changes. To solve this problem, we proposed a method using compressed electrical impedance sensing and discrimination analysis. We employed multiple excitation conditions like electrical impedance tomography, and investigated the effective excitation conditions. We then used both simulation and measurement data for efficient training process. In our experiment, we implemented a simulator and a measurement system with 16 electrodes and biological phantoms, and evaluated the discrimination rate for various impedance distribution by assuming muscle injury. As a result, we found that 6/120 excitation conditions are sufficient for detection of local impedance changes in a simple model and sufficient blending ratio of the measurement data to simulation data was 10.6% to perform 90% discrimination. The experimental result also indicated that the proposed method was robust for injury size, injury position, and body shape and 90% discrimination was achieved using 13/120 excitation conditions for complex models including skin, bone, and muscle area.

Soft pneumatic pouch actuators with simple structures and fabrication processes are being studied for application in soft robots. In addition, some research groups have tried to add sensors to the pouch actuators to estimate their states. In this study, we propose to embed a soft strain sensor made of liquid metal in the bladder of a pouch actuator made of stretchable styrene-ethylene-butadiene-styrene (SEBS) film, which can expand to a large extent under pressure to enable shape estimation. A method of processing the bladder of the pouch actuator to convert it into a sensor has yet to be proposed. We developed a fabrication process to form the small strain sensor in the SEBS film and evaluated the strain sensor's stretch characteristics. Finally, we confirmed that the deformation of a bending pouch actuator caused by pneumatic pressure is expressed in the electrical resistance of the embedded strain sensor. [ABSTRACT FROM AUTHOR]