In this paper, we propose to use facial electrical stimulation to control maximal voluntary contraction (MVC) of the upper limbs. The method is based on a body mechanism in which the contraction of the masseter muscles enhances MVC of the limb muscles. Facial electrical stimulation is applied to the masseter muscles and the lips. The former is to enhance the MVC by causing involuntary contraction of the masseter muscles, and the latter is to suppress the MVC by interfering with voluntary contraction of the masseter muscles. In a user study, we used electromyography sensors on the upper limbs to evaluate the effects of the facial electrical stimulation on the MVC of the upper limbs. The experimental results show that the MVC was controlled by the facial electrical stimulation. We assume that the proposed method is useful for sports athletes because the MVC is linked to sports performance.

Several benefits obtained using multiple robots in conversation have been reported in the human-robot interaction field. This paper first presents pre-trial results by which elderly people assigned a lower rating to a conversation with two robots than to one with a single robot. Observations of the trial suggest the hypothesis that an inappropriate spatial arrangement between robots and humans increases the workload in a conversation. Reducing the workload is important, especially when robots are used by elderly people. Therefore, we specifically examine the workload that is influenced by the spatial arrangement in group conversation. To verify the hypothesis, we use a NASA-TLX and a dual-task method to evaluate the workload and to conduct a comparative experiment in which the participant talks with two robots in two spatial arrangements. We also conduct a case study for elderly people in the same conversational conditions. From these experiments, we demonstrate that the spatial arrangement in which people cannot see both robots simultaneously increases their conversational workload and decreases their evaluation of the dialogue compared to a spatial arrangement by which people can see both robots simultaneously. We also show that the primary cause of the workload by positioning is not physical but mental.

Muscle fatigue monitoring is important for injury prevention in sports. Previous studies have shown that wearable electromyography (EMG) sensors on limb muscles can be used to monitor the level of muscle fatigue continuously. However, there are two main problems in using these sensors for sports. One is that users wearing them create motion artifacts that affect the sensor data. The other is that the sensors disturb limb motion. To address these problems, we propose a method for estimating biceps fatigue with an e-textile headband. There is a strong correlation between frowning and jaw clenching muscle activity and the physical efforts made when exercising. Our method uses both of EMG signals of the temporal muscles and motion artifacts. The former indicate jaw clenching and the latter indicate frowning. Experimental results show that the root mean square values calculated from the headband sensor values significantly increased when biceps were fatigued.

Social robots have been providing a number of customer services lately. For example, they can take the place of people as receptionists. When people interact they predict each others decision-making from the others actions and take suitable actions for the sake of the other. However, taking such actions is difficult for modern social robots. Therefore, our initial aim is to solve the problem of how to predict decision-making in human-robot engagement. Choosing a reception system as a case study to approach this goal, we created a new model to predict who will use the system. The model contains a state transition function based on observation studies. We evaluated the model though a controlled experiment and a simulation experiment, using field data on prediction performance and mental effect. The experiment results lead us to believe that the model can predict the decisions of others sufficiently well. We also found that a pedestrian who will not talk with a robot receptionist suffers a negative emotion when the pedestrian is greeted by a robot, but a method we propose prevents this. We suggest that the word suitable is related to negative emotion, a part of usability. By using our model in the future we will attempt to find a method that will enable a robot to learn suitable actions by itself.

"Mirroring" refers to the unconscious mimicry of another person's behaviors, such as their facial expressions. Mirroring has many positive effects, such as enhancing closeness and improving the flow of a conversation, which enriches the quality of communication. Our study set out to devise a means of evoking these positive effects in a video chat without any conscious effort of participants. We constructed a videophone system, called FaceShare, which can deform the user's face into a smile in response to their partner's smiling. That is, our system generates mirroring by producing a pseudo-smile through image processing. We conducted an experiment in which pairs of participants had brief conversations via FaceShare. The results implied that mirroring using the pseudo-smile lets the mimicker, whose face is deformed according to the expressions of their partner, feel a closeness, and improves the flow of the conversation for both the mimicker and the mimickee, who sees the mimicker's deformed face.

To effectively utilize gaze in one-to-many communication, robots must direct and avert their gaze with appropriate timing. However, few studies have focused on this aspect of communication because of the difficulty in detecting the position of many gaze recipients and directing appropriate gazes to each. This paper proposes a system of robotic eyes that can send averted or direct gazes simultaneously to multiple recipients by switching between convex and hollow eye shapes, which we call Transgazer.

Many studies have addressed the affective robot, a robot that can express emotion, in the field of human-robot interaction. Really useful applications, however, can only be designed if the effect of such expressions on the user are completely elucidated. In this paper, we propose a new useful application scenario for the affective robot that shares the user's experience and describe an experiment in which the user's experience is altered by the presence of the affective robot. As the stimulus, we use movie scenes to evoke 4 types of emotion: excitement, fright, depression, and relaxation. Twenty four participants watch different movies under three conditions: no robot present, with robot that offers appropriate emotional expression, and with robot that has random emotional expression. The results show that the participants watching with the appropriate emotion robot experienced stronger emotion with exciting and relaxing movies and weaker emotion with scary movies than is true without the robot. These changes in the viewer's experience did not occur when watching with the random emotion robot. From the results, we extract design points of affective robot behavior for enhancing user experience. This research is novel in terms of examining the impact of robot emotion, seen as appropriate by the viewer, on the viewer's experience.

We propose shared emotional experience agents. They enhance the user's emotional experience by emotional contagion. Our experiment has 12 participants watch videos together with a robot that expresses an emotional state by body and voice. The results suggest that the affective robot will make user more excited and relaxed and make user less depressed and afraid than they view it alone.