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Purpose: A remedy for ankle osteoarthritis is artificial joint replacement surgery. By estimating the relative positional difference (alignment) between the bone before and after deformation, precise artificial joint replacement surgery can be performed. By using the estimated alignment, an artificial ankle joint can ensure high satisfaction with less pain and can perform necessary functions. Although bone alignment is currently estimated from X-rays and computed tomography (CT) images, it is difficult to measure three-dimensional (3D) data from two-dimensional (2D) images. Although 3D data can be estimated using a 2D–3D registration method, it requires capturing the bone images multiple times and imposing considerable burden on the patient. In this paper, we propose a method to estimate the 3D bone alignment based on the size of the bone using principal component analysis (PCA), which requires scanning only one data. Method: In the proposed method, PCA is used to create a 3D bone model based on the bone thickness, and the bone alignment is estimated by the Go-ICP algorithm. In this study, the images of the foot were captured using a CT device, and the 3D bone model was created by stacking CT images. For improving the accuracy of the alignment, a reference model based on the bone thickness was created using PCA. Subsequently, the bone was overlapped and the alignment was estimated. Result: For the evaluation of the accuracy of alignment in the proposed method, three types of methods were used to create a bone model. The proposed method was found to be the most accurate with respect to the true value in five of the six evaluation criteria. In addition, the alignment of the tibiofibular joint was evaluated using the proposed method. Regarding the displacement in the [Formula: see text]-axis direction, there were significant differences in both Stage 3B and Stage 4 compared with the healthy subjects. In addition, the magnitude of rotation in the [Formula: see text]-axis direction showed a significant difference in stage 3B as compared with a healthy subject. Conclusion: Using the proposed method, we have shown that bone alignment can be estimated three-dimensionally by scanning the bone data once only. In addition, by comparing with the reference model using PCA based on the thickness of the bone, the accuracy of alignment is improved as compared with the reference model, which is not based on the bone thickness.

Communication robots have been introduced in nursing care, education, and the hospitality sector. In the future, robots will be increasingly integrated into human society, with more opportunities to interact closely with humans. Therefore, investigating the symbiosis between humans and robots is critical. Touch, including actions, such as shaking hands, holding hands, and touching shoulders are common in most societies. These actions are called the social touch and are common modes of communication. Social touch not only conveys emotions and intentions but also mental and physical effects. Touch considerably influences social relationships: for example, by creating positive impressions and enabling the fulfillment of requests. Since the development of communication robots and other robots capable of physical contact, touch communication between humans and robots has been extensively studied. Although studies have revealed that touching a robot positively influences the impression regarding the robot and induces a relaxed feeling, negative perceptions related to trust on the robot have been reported. Thus, touch interactions between humans and robots are yet to be fully understood. Studies have focused on the effects of touch, such as touching the robot or being touched by the robot. Although interactions with robots that respond to touch, such as hugging behavior, have been studied, few studies have examined the psychological effects of robot responses to other types of touch such as hitting, stroking, and grasping. In this study, a humanoid robot was used to investigate how the reactive behavior exhibited by the robot in response to touch by a participant affects the degree of favorability and intellectual impression toward the robot as well as the sense of accomplishment regarding communication. Participants exhibited high favorability, feeling of relief, and willingness to continue the interaction with robots that exhibited appropriate reactions to the touch of participants. Participants exhibited a positive impression when they decided the touch gesture of the robot rather than when instructed on how to touch it. The results of this study can provide guidelines for improving the design and utilization of robots, such as therapeutic robots, that work alongside humans.

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