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There are few studies that have conducted comprehensive verification of the physiological and psychological effects of different textures of chilled confectioneries by means of biometric measurements and subjective evaluation. The effects of confectionery texture are still unclear. Therefore, this study aimed to clarify the effects of different textures on the activity of autonomic nervous system, the brain, and muscles, and emotion by simultaneously measuring changes over time in various biological information and assessing subjective evaluation given by the tasters during consumption of different types of ice cream with monaka shell with varying water content. Participants answered a subjective evaluation questionnaire and rested for 60 s, and then performed the task. The monaka ice cream consisted of 9 blocks, each of which was eaten in 20 s. Afterwards, the participants rested for 60 s and completed a subjective evaluation questionnaire. Near-infrared spectroscopy was used to measure brain activity during eating, electromyography to measure muscle activity, and electrocardiography equipment to analyze heart rate variability. Eating monaka shell with low water content significantly activated cerebral blood flow in the right hemisphere when the first and sixth blocks were eaten. A significant trend was observed in LF/HF, which is considered an index of sympathetic nerve activity. In the mastication force test, the participants chewed significantly more strongly on ice cream with a high water content monaka shell than those with a low water content. During mastication, the participants who consumed ice cream with the low water content shell tended to use slow muscles more than those who consumed ice creams with high water content shell. The questionnaire showed that both the increase in degree of emotions such as surprise and excitement and the decrease in the degree of emotions such as sadness and depression were larger when the participants consumed ice cream with a high water content shell than those with a low water content shell. The results suggest that monaka shells with a low water content induce a more relaxed state and pleasant emotions than those with a high water content.

In the manufacturing industry, the transfer of knowledge of expert is an issue because the number of experts is decreasing. In order to support knowledge transfer, various support systems have been developed. However documenting knowledge and determining the level of system users is a concern. This study aims to develop a technique for knowledge extraction and user level judgement using gaze measurement. In order to develop these techniques, the difference of gaze between expert and beginner need to be evaluated. In this study, the gaze of experts and beginners were measured in relation to the vortex exploration skill in the task to explore for vortices which is a typical phenomenon from fluid simulation results. 6 fluid simulation result pictures were presented to experts and beginners, and their gaze was measured. Our result suggested that the expert observe vortex area and area without vortex long time. Beginner did not observe the horizontal elliptical vortices many times, as a result they often missed it. Beginner’s gaze transfer between vortices area many times than expert’s. Expert’s pupil size was larger than beginner’s. These results imply that the experts observe the simulation result image widely, find a place where there is a possibility of a vortex, and concentrate long time to judge whether it is a vortex. On the other hand, the beginners find a place where there is a possibility vortex in the simulation result image and compare other area where there is a possibility vortex to judge whether it is a vortex. By utilizing the gaze measurements, the method of exploring the vortex of the experts was revealed and it was found that user’s level can be judged.

Several training methods have been developed to obtain motion information during real-time walking and feed it back to trainees who adjust their gait to ensure that the measured gait parameters approach target value, which may not always be suitable for every trainee owing to physical differences between individuals. This paper proposes a method of setting this target value considering these physical differences and discusses the usefulness of the gait training method, wherein a multichannel deep convolutional neural network (MC-DCNN) gait classification model constructed by learning ideal or non-ideal gait features beforehand is used for trainee gait classification. Activation maximization is applied to the MC-DCNN model; data wherein the ideal walking features are activated are generated based on trainee gait data. However, the amounts of features to be activated to generate a possible and natural gait are restricted. The original trainee gait, beyond individual physical differences, and gait data generated based on the original gait data seem to yield the target value considering the physical differences among individuals. This study focused on gait related to stumbling. To verify its usefulness, a multivariate gait dataset consisting of kinematic and kinetic indices labeled as “gait rarely associated with stumbling” or “gait frequently associated with stumbling” was divided into a training set, validation set, and test set. The MC-DCNN model learned gait features for multivariate gait data classification in the training set. It classified the gait with 96.04±0.12% accuracy against the validation set. Finally, by applying the proposed method to the multivariate gait data contained in the test set, we generated multivariate gait data classified as “gait rarely associated with stumbling” based on the input data. In addition, the generated multivariate gait data include motion that increases the thumb-to-ground distance and describe possible and natural gait considering the physical differences among individuals.

Application of exposure to 50/60 Hz magnetic fields (MFs) has been conducted in the treatment of muscle pain and fatigue mainly in Japan. However, whether MFs could increase blood flow leading to muscle fatigue recovery has not been sufficiently tested. We investigated the acute effects of a 50 Hz sinusoidal MF at Bmax 180 mT on hemodynamics, electrocardiogram, and vascular endothelial function in healthy young men. Three types of regional exposures to a 50 Hz MF, i.e., forearm, upper arm, or neck exposure to MF were performed. Participants who received three types of real MF exposures had significantly increased ulnar arterial blood flow velocity compared to the sham exposures. Furthermore, after muscle loading exercise, MF exposure recovered hemoglobin oxygenation index values faster and higher than sham exposure from the loading condition. Moreover, participants who received real MF exposure in the neck region had significantly increased parasympathetic high-frequency activity relative to the sham exposure. The MF exposure in the upper arm region significantly increased the brachial artery flow-mediated dilation compared to the sham exposure. Computer simulations of induced in situ electric fields indicated that the order-of-magnitude estimates of the peak values were 100–500 mV/m, depending on the exposure conditions. This study provides the first evidence that a 50 Hz MF can activate parasympathetic activity and thereby lead to increase vasodilation and blood flow via a nitric oxide-dependent mechanism. Trial registration: UMIN Clinical Trial Registry (CTR) UMIN000038834. The authors confirm that all ongoing and related trials for this drug/intervention are registered.

Mobility scooters are three or four-wheeled electric-motor-driven wheelchairs with a handlebar for steering. In the use environment of a mobility scooter, there may be many obstacles that need to be avoided, such as pedestrians on a narrow sidewalk or cars on the edge of the road. These obstacles not only interfere with smooth driving but also induce mental strain on the user such as fear and anxiety, which may cause a decrease in comfort and an accident. The purpose of this study is to estimate physical obstacles in the road environment when driving a mobility scooter from operation information and physiological information of the user obtained during driving. We measured skin conductance, manipulation amount of accelerator, steering torque, and acceleration value in the horizontal plane when driving on a few courses with physical obstacles. We tried to build a machine learning model that estimates the type of physical obstacles in the course based on these time-series data by using a random forest classifier.

Several training methods have been developed to acquire motion information during real-time walking; these methods also feed the information back to the trainee. Trainees adjust their gait to ensure that the measured value approaches the target value, which may not always be suitable for each trainee. Therefore, we aim to develop a gait feedback training system that considers individual differences, classifies the gait of the trainee, and identifies adjustments for body parts and timing. A convolutional neural network (CNN) has a feature extraction function and is robust in terms of each feature position; therefore, it can be used to classify a gait as ideal or non-ideal. Additionally, when the gradient-weighted class activation mapping (Grad-CAM) is applied to the gait classification model, the output measures the influence degree contributed by the trainee’s each body part to the classification results. Thus, the trainee can visually determine the body parts that need to be adjusted through the use of the output. In this study, we focused on gaits related to stumbling. We measured the kinematics and kinetics data for participants and generated multivariate gait data, which were labeled as “gait rarely associated with stumbling” class or “gait frequently associated with stumbling” class using clustering with dynamic time warping. Next, the multichannel deep CNN (MC-DCNN) was used to learn the gait using the multivariate gait data and the corresponding classes. Finally, the data for verification were input into the MC-DCNN model, and we visualized the influence degrees of each place of the multivariate gait data for classification using Grad-CAM. The MC-DCNN model classified gaits with a high accuracy of 97.64±0.40%, and it learned the features that determine the thumb-to-ground distance. The output of the Grad-CAM indicated body parts, timing, and the relative strength of features that have an important effect on the thumb-to-ground distance.

This study aims to examine the benefit of visual fatigue evaluation based on prefrontal cortex (PFC) measurement by near infrared spectroscopy (NIRS), and to evaluate fatigue on various colored LED backlit text. In our method, eight adult participants read a LED backlit text 10 minutes in a dark room. Before and after task, subjective fatigue questionnaire “Jikaku-sho shirabe”, subjective visual fatigue questionnaire (SVF), and the critical flicker-fusion frequency (CFF) were measured. The time-course of oxy-Hb in the PFC was measured using a 22-channel NIRS. Heart rate variability (HRV) was measured to access an autonomic nervous system balance. Six types of white LEDs were used for backlighting: general white as a control (W), high color-rendering white (WH), bluish white (WB), reddish white (WR), greenish white (WG), and yellowish white (WY). In our results, correlation analysis suggested that the development of central fatigue is related to deactivated condition in the mPFC, and the development of subjective visual fatigue is related to deactivated condition in the LPFC. In comparison between LED treatments, in WH condition, high subjective central fatigue, CFF decay and LF/HF were revealed, and the PFC inactivated. In WG condition, low subjective central fatigue and CFF decay revealed. Our findings suggested that participants get tired on high color-rendering white LED backlit text, and were less tired in greenish white LED backlit text. Also, NIRS provides benefits in the evaluation of visual fatigue.

We proposed an advanced mesh generation technique that reuses the proven analysis models by similar sub-part search. The purpose of this research is to reduce interactive mesh improvement work time and to comply with the mesh specifications. It is our feature technique to search sub-parts similar to the archived sub-parts of proven models from new design CAD. In this technique, the similar sub-parts are retrieved from a CAD model described by boundary representation and made correspondence relation surface pairs of a retrieval model (proven model) and a target model (CAD of new design). A similarity score is based on the attributed graphs of a retrieval model and a target model. And, this score is calculated by a geometrical similarity and topological similarity. If there is such search noise, unreusing sub-parts must be canceled by interactive operation. This is an obstacle to automation. Therefore, with the goal of eliminating search noise, we developed a technique to improve the accuracy of similar partial shape retrieval. By quantifying the geometric relationships such as concentric circles and face-to-face distance as similarity, high precision could be realized. It was applied to a door switch cover part of an automobile which is a verification model, and it was confirmed that search noises disappeared.

Emotion is an internal and subjective experience that plays a significant role in human life. There are several methods of recognizing emotions in people, the most authentic of which is using physiological signals, as they are beyond one’s control and strongly correlated with human emotions. This study aims to develop an emotion recognition system based on three physiological signals, namely, brainwave, heartbeat, and facial muscular activity. It utilizes deep neural network (DNN) and the T method of Mahalanobis-Taguchi system (MTS) to process the multiple physiological signals and further recognize the states of human emotion. As such, nine emotions are effectively recognized on a two-dimensional model through the DNN, then compared against several other algorithms, such as MTS, SVM, Naive Bayes, and K-means, where its superior accuracy is validated. Moreover, although the T method only improves the classification accuracy on the valence state, it rather obtains the intensity of emotion in different states. Furthermore, in this study, the proposed DNN is implemented into a wide range of applications for an accurate understanding of the human emotional states, whereas the T method is utilized to respond to the emotional intensity in different states. Finally, a real-time emotion recognition system is developed with DNN as the classifier; this system can directly monitor the variation of the human emotion through reliable and objective emotion analysis results from the physiological signals. Thus, the method can provide useful treatment effect information for robots or assistive apparatus serving activities of daily living.

This paper proposes an advanced mesh generation technique that reuses the proven analysis models by searching for similar sub-parts. The purpose of this development is to reduce interactive mesh improvement work time and to comply with the mesh specifications. In particular shell mesh generation, working time of complex thin parts such as resin parts is long, which causes issues for front-loading. Furthermore, quality improvement and standardization of analysis models are required because the general designers have to manage V&V (Verification & Validation). This technique consists of two distinctive techniques. First, it is the technique to search the subparts from newly designed CAD which have similar shape with the archived feature sub-parts contained in the proven CAD models. In this technique, the similar sub-parts are retrieved from a CAD model described by boundary representation and made correspondence relation surface pairs of a retrieval model (proven model) and a target model (CAD of new design). A similarity score is calculated based on geometrical similarity and topological similarity. Geometric similarity is based on geometric information such as areas and perimeters. Topological similarity is based on the surface connection differences. Second, mesh can be generated automatically by arranging and merging the know-how meshes based on the relationship of the surfaces by similar sub-parts search technique. Experimental results show that this technique can efficiently generate a mesh without interactive mesh improvement operation which was conventionally taken several hours.

Due to the growing elderly population in many developed countries like Japan, assistive devices are increasingly needed to overcome the difficulties of their activities of daily living (ADL). The motion of standing up places a particular burden on the ankle and knee joints and connects static motions (e.g., sitting and lying) and kinetic motions (e.g., walking and climbing up/down the stairs). In our previous research, two types of standing-up assistance apparatuses were introduced according to the suitable standing-up motions. However, these devices are bulky and cannot be widely used in practical settings such as bus terminals. Regarding the suitable standing-up motions of the elderly in the previous literature, a standing-up apparatus with a pantograph mechanism is introduced to diminish the size of the mechanism based on three design principles: (1) the trajectory of the user's COG is an arc; (2) the trajectory of the user's hip joint while standing up is a straight line at an angle of 45 [deg] from the horizon; and (3) the user is supported until the knee angle reaches 60 [deg]. Simulations showed that the load on knee and ankle joint is decreased, and user may stand up easily with our proposed apparatus. A prototype of the apparatus that may be installed on various chairs in public was fabricated. Considering that the apparatus may be used in places without electric power supply, the apparatus is made simply with links and a gas spring instead of electric actuators. Experimental measurements of the trajectories of the center of gravity (COG) and hip joints show that the proposed apparatus may help users to stand in a way that minimizes stress on their lower-body joints.

Wearable assistive devices have been receiving considerable attention in academic circles. To make these devices efficient, we need additional research on the service lives of the mechanical elements used in these devices. The wearers of these devices frequently encounter unexpected movements that lead to motor failure in the devices. The purpose of this study is to develop an overload protection mechanism using a torque limiter, which can eliminate the overload torque delivered in the reverse direction to effectively prevent the device from breaking and ensure the safety of the user. To improve the service life of assistive walking devices, we designed a sandwich mechanism for the final gear of the servo motor. We made the material from rubber and configured it between a pair of circular plates. The surface tractive force delivered the required torque. When the surface load exceeded the maximum friction force, the circular plates slipped and protected the device. In this paper, we implement a torque limiter and prove its durability by performing experiments using two circular plate designs, one with grooves type and another without grooves type. We also use various materials to assess the applicability of the assistive walking device. The findings indicate that the with grooves type gives better torque performance; it achieves the same rated torque as the servo motor. Thus, this study recommends that with grooves type is particularly suitable for the elderly who require high assistive power. On the other hand, without grooves type is suitable for users who employ the device for extended periods because this type has an excellent service life. Our experiment proves that the torque limiter that we developed can withstand the load torque over 300 times for situations involving the loss of balance such as stumbling and slipping. Finally, we experimentally validate the improvement of walking performance by using this torque limiter.

Recently, the viewpoint of service has become widespread. In learning domains, service providers have been required to adopt the viewpoint and to provide values co-created by teachers and learners. However, production by a service provider means the generation of potential value, whereas usage by a service receiver implies the generation of real value. That is, a receiver creates value independent of the value generated by a provider. Indeed, value co-creation takes place in a joint sphere where providers and customers interact with each other. Thus, service providers must attempt to generate the potential value through service design and play a role of co-producer of the real value in the interactions between the providers and the receivers. In the current study, we developed an ontology to share the knowledge on value co-creation and the information related to the interactions between the providers and the receivers. In concrete terms, we proposed ontological descriptions of receiver states for sharing knowledge in learning service design, and conceptualized elements of consensus building and value co-creation, according to the conceptual model of value co-creation proposed in a previous study. In addition, concepts pertaining to academic emotions are also described to represent contents of consensus building. Then, we demonstrated instances of a consensus building, which is extracted from conversations during counseling by a teacher (mentor) and a learner. As a result, we obtained a metamodel for co-design processes in the learning service design, and a conceptual framework of the knowledge sharing on learning states including academic emotions by the ontological descriptions.

It is desired the method to analyze ordinary citizen's mental state and transition at social various situations, and the business applicability using that is expected. In Europe, the FilmStim database which can arouse specific emotion was edited. In this study, we examined whether the FilmStim can be applied to Japanese. And we investigated the relationship between brain activity and positive and negative emotion by using NIRS. It was indicated the possibility that the emotional score of European can apply to Japanese by explaining contents of film. When arousing positive and negative emotion, it was indicated that oxy-Hb was changed at outer part of right brain. This result suggests that measuring brain activities can be used to distinguish whether positive or negative emotion is experienced.

In this paper, we analyze the relationship between brain activity and accuracy of replicating actions in the process of embodied knowledge acquisition. Subjects learned a series of actions as fundamental embodied knowledge as a experiment. Remembering and executing the actions, oxy hemoglobin increase in dorsolateral prefrontal area and decrease in frontal pole. Subjects watched a video crip of a working procedure, and executed the same series of actions as another experiment.. We conducted this experiment twice. After the first experiment, we set up three practice terms. In the observation task, oxy hemoglobin stabilize at a low level in dorsolateral prefrontal area and frontal pole with elevation of accuracy of replicating actions. In the execution task, oxy hemoglobin increase in dorsolateral prefrontal area and decrease in frontal pole with elevation of accuracy of replicating actions. These results suggest frontal pole relate self body imaging and dorsolateral prefrontal area relate working memory, and activity in these areas changes during the process of embodied knowledge acquisition.

We developed a new method that can diagnose damage on a gear tooth surface using a laser beam without a rotary encoder. The method procedure is as follows: 1) The tooth bottom, the tooth tip and their two median values are detected using the differential values of the laser reflection data. 2) The gear rotation speed is calculated with these four positions, and interpolated according to the rotation fluctuation. 3) Using the calculated gear rotation speed, the measured data can be converted to the corresponding gear rotation angles. Thus we can diagnose the damage of the gear tooth surface precisely and can easily set up the experimental measurements without being influenced by rotational fluctuation. To confirm the validity of the method, we conducted the diagnosis experiment and we created contour maps to show the diagnosis accuracy variation according to the fluctuations of the amplitude and cycle. Based on these maps, we found that the diagnosis accuracy of the damage size is the same irrespective of the presence or absence of a rotary encoder. The diagnosis accuracy of the damage location without using a rotary encoder is lower than the result obtained using a rotary encoder because we assumed that the detection of the damage start point is delayed using this new method. Furthermore, we defined the limit using the conditions of this method from the sampling theorem; the validity of this definition could also be confirmed from the contour map.

In this study, we developed an intuitive remote-controlled manipulator system that was operated using a touch panel display and a mouse. We examined its application possibility to pick out the shoot apical meristem from sprouting potatoes. The shoot apical meristem is not easily affected by plant viruses. Therefore, we can obtain a virus-free seedling that has a high production efficiency by culturing this part. This technique is called “mericlone” and is known widely in agriculture; however, it is tedious because of the precision work involved with a microscope. Thus, our system not only reduces the burden on the technician but also has high precision control and saves space. In this study, using the loop-mediated isothermal amplification method, we confirmed that we could get the potato meristems that do not contain Potato Virus X. The newly designed primer set can achieve results more rapidly, more easily, and with higher sensitivity than other virus detection methods, thus indicating the possibility of industrial implementation.

In the present paper, we describe the measurement of brain activation response during lathe operation in a VR lathe environment and an actual lathe environment by near-infrared spectroscopy. In the frontal lobes and the motor cortex, oxyHb tended to increase during the operation in both the VR lathe environment and the actual lathe environment. The results show that the brain activation response during the performance of lathe operation in the VR lathe environment was very similar to that which occurs during lathe operation in the actual lathe environment.

In recent years, as part of the remarkable development of electronic techniques, electronic control has been applied to various systems. Many sensors and actuators have been implemented into those systems, and energy efficiency and performance have been greatly improved. However, these systems have been complicated, and much time has been required to develop system controllers. In this paper, a method of automatic controller design for those systems is described. In order to automate the design of an electronic controller, an evolutionary hardware is applied. First, the framework for applying the genetic algorithm to the automation of controller design is described. In particular, the coding of a chromosome is shown in detail. Then, how to make a fitness function is represented, with an air conditioner as an example, and the controller of the air conditioner is developed automatically using our proposed framework. Finally, an evolutionary simulation is performed to confirm our framework.

Speed and efficiency are necessary in the field of mechanical design. CAD/CAM/CAE technologies have advanced and attention has also been paid to increasing the efficiency of data sharing and agent processes in the web environment. In this paper, Semantic Web technology is used to enable the sharing of metadata. The metadata consists of design documents and design formulas, with additional semantic information inserted. Mathematical information is expressed by adding metadata into conventional mechanical design formulas using a Resource Description Framework (RDF). The design formulas are later written in MathML (Mathematical Markup Language) for the sake of data sharing. In this way, data sharing and advanced searching is made easy, because the relevant information is made machine readable in the web environment. The calculation of design formulas is made possible using a mathematical processing system, thus increasing the efficiency of mechanical design.

The environment in which Japanese industry has achieved great respect is changing tremendously due to the globalization of world economies, while Asian countries are undergoing economic and technical development as well as benefiting from the advances in information technology. For example, in the design of custom-made casting products, a designer who lacks knowledge of casting may not be able to produce a good design. In order to obtain a good design and manufacturing result, it is necessary to equip the designer and manufacturer with a support system related to casting design, or a so-called knowledge transfer and creation system. This paper proposes a new virtual reality based knowledge acquisition and job training system for casting design, which is composed of the explicit and tacit knowledge transfer systems using synchronized multimedia and the knowledge internalization system using portable virtual environment. In our proposed system, the education content is displayed in the immersive virtual environment, whereby a trainee may experience work in the virtual site operation. Provided that the trainee has gained explicit and tacit knowledge of casting through the multimedia-based knowledge transfer system, the immersive virtual environment catalyzes the internalization of knowledge and also enables the trainee to gain tacit knowledge before undergoing on-the-job training at a real-time operation site.

Methods such as the Predicted Mean Vote and Standard New Effective Temperature were developed to evaluate thermal comfort. However, radiation and convection of heat due to factors such as sunlight or air cycle are strong in indoor environments. Moreover, the thermal environment in such indoor environment is non-uniform and locally inhomogeneous, which makes evaluation thermal comfort difficult. We aim to evaluate the local thermal environment by analyzing brain activity. The final goal is to develop an air conditioning control system in non-uniform and locally inhomogeneous thermal environment by brain activity. In this paper, we describe analysis of brain activity during local cold stimulation. We measured oxyhemoglobin (oxyHb) levels in the prefrontal cortex and the primary somatosensory cortex while subjects touched aluminum plates that were cooled or heated to different temperatures. The results show that oxyHb changes in the prefrontal cortex vary according to the temperature of the aluminum plates.

Independence support robots using multi joint manipulators are thriving in the field of welfare. Keyboards or joysticks are generally used in the remote operation of the multi joint manipulators. The posture of the multi joint manipulators can be ordered by the angle of the joystick or preconfigured key assignment. These control systems have a problem, however, that the number of operable joints is limited to the number of joystick axes or keyboard buttons. In this study, we propose a remote control system for the multi joint manipulator using touch panel and gyroscope sensor. We call the system TGC (Touch Gyro Control). Miniaturization and performance increase are in progress to various sensors such as gyroscope and touch panel with the development of MEMS technology in recent years. In addition, these sensors have spread rapidly in our living environment. In this study, we use touch panel and gyroscope sensor mounted on a smartphone. The TGC system can control rotational movement of the manipulator using the orientation of the smartphone, translational movement in the horizontal plane using the drag operation of the touch panel display and translational movement in the vertical plane using up and down motion of the arm which is gripping the smartphone. For the quantitative evaluation, we experimented with 3D pointing tasks using the TGC and compared to the conventional method of button-type control. The result of the experiment indicated that the TGC could point faster than conventional button-type method. In addition, we also experimented with the task that grip and transfer screws into a box using 6-DOF manipulator which is controlled by above two methods. The result of this experiment also showed the advantage of the TGC. The usefulness of the TGC for the operation of the multi joint manipulator is verified in this research.

Ride comfort is an important issue in improving passenger comfort in an automobile. Quantifying ride comfort is difficult because it affects a person's emotions and physiology. In this paper, we measure brain activities using near-infrared spectroscopy to clarify the features of brain activities while sensing vibration. Hopefully, the results obtained in this study can be applied to quantify subjective evaluation for ride comfort. Moreover, we measured brain activities while sensing vibrations which are uncomfortable and not uncomfortable vibrations. Uncomfortable and not uncomfortable vibrations were determined on the basis of sensory evaluation. Results showed that the concentration of oxygenated hemoglobin (oxy-Hb) levels in the prefrontal cortex change with the sense of vibration. In addition, during uncomfortable vibration, the oxy-Hb level declined more than that while sensing not uncomfortable vibrations. In addition, we measured brain activities while sensing a vibration which is divided over subject's feeling to the vibration and found that oxy-Hb of the subjects sensing uncomfortable vibration declined in the prefrontal cortex. Therefore, we infer that decline of oxy-Hb in the prefrontal cortex is relative to an uncomfortable feeling.