When humans generate stimuli voluntarily, they perceive the stimuli more weakly than those produced by others, which is called sensory attenuation (SA). SA has been investigated in various body parts, but it is unclear whether an extended body induces SA. This study investigated the SA of audio stimuli generated by an extended body. SA was assessed using a sound comparison task in a virtual environment. We prepared robotic arms as extended bodies, and the robotic arms were controlled by facial movements. To evaluate the SA of robotic arms, we conducted two experiments. Experiment 1 investigated the SA of the robotic arms under four conditions. The results showed that robotic arms manipulated by voluntary actions attenuated audio stimuli. Experiment 2 investigated the SA of the robotic arm and innate body under five conditions. The results indicated that the innate body and robotic arm induced SA, while there were differences in the sense of agency between the innate body and robotic arm. Analysis of the results indicated three findings regarding the SA of the extended body. First, controlling the robotic arm with voluntary actions in a virtual environment attenuates the audio stimuli. Second, there were differences in the sense of agency related to SA between extended and innate bodies. Third, the SA of the robotic arm was correlated with the sense of body ownership.

As one of the facial expression recognition techniques for Head-Mounted Display (HMD) users, embedded photo-reflective sensors have been used. In this paper, we investigate how gaze and face directions affect facial expression recognition using the embedded photo-reflective sensors. First, we collected a dataset of five facial expressions (Neutral, Happy, Angry, Sad, Surprised) while looking in diverse directions by moving 1) the eyes and 2) the head. Using the dataset, we analyzed the effect of gaze and face directions by constructing facial expression classifiers in five ways and evaluating the classification accuracy of each classifier. The results revealed that the single classifier that learned the data for all gaze points achieved the highest classification performance. Then, we investigated which facial part was affected by the gaze and face direction. The results showed that the gaze directions affected the upper facial parts, while the face directions affected the lower facial parts. In addition, by removing the bias of facial expression reproducibility, we investigated the pure effect of gaze and face directions in three conditions. The results showed that, in terms of gaze direction, building classifiers for each direction significantly improved the classification accuracy. However, in terms of face directions, there were slight differences between the classifier conditions. Our experimental results implied that multiple classifiers corresponding to multiple gaze and face directions improved facial expression recognition accuracy, but collecting the data of the vertical movement of gaze and face is a practical solution to improving facial expression recognition accuracy.

With advancements in robotics, systems featuring wearable robotic arms teleoperated by a third party are appearing. An important aspect of these systems is the visual feedback provided to the third party operator. This can be achieved by placing a wearable camera on the robotic arm's “host,” or Main Body Operator (MBO), but such a setup makes the visual feedback dependant on the movements of the main body. Here we introduce a VR system called Parasitic Body to explore a VR shared body concept representative of the wearable robotic arms “host” (the MBO) and of the teleoperator (here called the Parasite Body Operator (PBO)). 2 users jointly operate a shared virtual body with a third arm: The MBO controls the main body and the PBO controls a third arm sticking out from the left shoulder of the main body. We focused here on the perspective dependency of the PBO (indeed, the PBO view is dependant of the movement of the MBO) in a “finding and reaching” task.