Falls and fall risk management are challenges that are increasing in an aging society, exacerbated by the decreasing availability of care professionals to provide suitable fall management plans. Technology may provide a solution to this, with robotics and vision systems receiving increased attention. A pilot study was conducted using a vision system mounted on a Turtlebot 4, MoveNet, and different machine learning algorithms to assess a Timed Up and Go (TUG) test. The system was evaluated on the performance of a previously trained action classifier and by comparing times for the different phases of the TUG test from the output of the model with the output from the QTUG test acquired by IMU sensors worn by the participants. The results showed the system could determine if the person was sitting, in transition, or standing with high accuracy (97.09%) with higher levels of consistency for participants between tests than the QTUG. This demonstrates that the system is not only advantageous requiring minimal user input but also can match the performance of wearable sensors that are considered the "gold standard" for TUG tests.

This paper describes the bipedal humanoid robot that makes human laugh with its whole body expression and affect human's psychological state. In order to realize "Social interaction" between human and robot, the robot has to affect human's psychological state actively. We focused on "laugh" because it can be thought as a typical example for researching "Social interaction". Looking through a Japanese comedy style called "manzai" or the art of conversation, we picked out several methods for making human laugh. Then we made several skits with the advice of comedians, and made the whole body humanoid robot perform them. Results of experimental evaluation with these skits shows that the robot's behavior made subjects laugh and change their psychological state seen as a decrease of "Depression" and "Anger".

Humanoid robots have this formidable advantage to possess a body quite similar in shape to humans. This body grants them, obviously, locomotion but also a medium to express emotions without even needing a face. In this paper we propose to study the effects of emotional gaits from our biped humanoid robot on the subjects' perception of the robot (recognition rate of the emotions, reaction time, anthropomorphism, safety, likeness, etc.). We made the robot walk towards the subjects with different emotional gait patterns. We assessed positive (Happy) and negative (Sad) emotional gait patterns on 26 subjects divided in two groups (whether they were familiar with robots or not). We found that even though the recognition of the different types of patterns does not differ between groups, the reaction time does. We found that emotional gait patterns affect the perception of the robot. The implications of the current results for Human Robot Interaction (HRI) are discussed.

Neurologic examination procedures require not only abundant knowledge but also prominent skills. During medical education and training, several methods will be put to use such as watching video, reading books, making use of the simulated patient (SP), and so on. These can help medical staffs, especially novices, to master the skills and accumulate experiences. To make up for the drawbacks of the above methods, such as lack of active interactions, limitation of multi-symptom reproductions, etc, the medical training simulators have been developed to improve training effectiveness. However, most of these simulators only mimic the symptoms. They have no the abilities to show the pathology of diseases. This limits the training effectiveness. In this paper, we propose an elbow robot named WKE-1(Waseda Kyotokagaku Elbow Robot No.1) for neurologic examination training as one part of the whole body patient robot named WKP (Waseda Kyotokagaku Patient). In this robot, we simulate various symptoms occurring during the examination of elbow force, biceps tendon reflex, involuntary action, and also make a physiological neurological model to simulate the pathology of the nervous system. Taking advantage of this robot, the trainee can get a systematic training on both the skills and knowledge. Finally, we take a set of experiments to verify our proposed mechanism and system. The experimental results lead to the consideration that the approach is worth following in further research.

The understanding of emotions in humans is really important in the Human-Robot Interaction field. The affective state of a person can be expressed in several ways, one of them being through the way we walk and our gait can convey emotional clues in social context. Those clues can be used to improve the personal interactions with our peers or add meaning to any message we want to express. However, only a few studies in humanoid robotics were done on the effects of the emotions on the walking. In this paper, we propose to assess the emotional walking patterns created from motion capture data with a survey. Those patterns represent different emotions (sadness, happiness) with different intensities (middle, high and exaggerated). Those emotional walking patterns achieved a high recognition rate of the emotions and the subjects (N=13) could recognize whole body emotions without facial expression on our humanoid robot. Additionally, we found out that at first people might perform poorly at recognizing emotions and their intensities but can get better, even without correction or feedback on their performances.

A complex relationship exists between national cultural background and interaction with robots, and many earlier studies have investigated how people from different cultures perceive the inclusion of robots into society. Conversely, very few studies have investigated how robots, speaking and using gestures that belong to a certain national culture, are perceived by humans of different cultural background. The purpose of this work is to prove that humans may better accept a robot that can adapt to their specific national culture. This experiment of Human-Robot Interaction was performed in Egypt. Participants (native Egyptians versus Japanese living in Egypt) were shown two robots greeting them and speaking respectively in Arabic and Japanese, through a simulated video conference. Spontaneous reactions of the human subjects were measured in different ways, and participants completed a questionnaire assessing their preferences and their emotional state. Results suggested that Egyptians prefer the Arabic version of the robot, while they report discomfort when interacting with the Japanese version. These findings confirm the importance of a culture-specific customisation of robots in the context of Human-Robot Interaction.

Performing laparoscopic surgery requires several skills which have never been required for conventional open surgery, surgeons experience difficulties in learning and mastering these techniques. Various training methods and metrics have been developed in order to assess and improve surgeon's operative abilities. While these training metrics are currently widely being used, skill evaluation methods are still far from being objective in the regular laparoscopic skill education. This paper proposes a methodology of defining a model to objectively evaluate surgical performance and skill expertise in the routine laparoscopic training course. Our approach is based on the processing of kinematic data describing the movements of surgeon's upper limbs. An ultra-miniaturized wearable motion capture system (Waseda Bioinstrumentation system WB-3), therefore, has been developed to measure and analyze these movements. The skill evaluation model was trained by using the subjects' motion features acquired from WB-3 system and further validated to classify the expertise levels of the subjects with different laparoscopic experience. An experiment for training fundamental laparoscopic psychomotor skill was elaborated by using laparoscopic box trainer. Preliminary results show that, the proposed methodology can be efficiently used both for quantitative assessment of surgical ability, and for the discrimination between expert surgeons and novices.

In this paper we propose the basic concept of a tele-presence system for two (or more) anthropomorphic robots located in remote locations. As one robot interacts with a user, it acquires knowledge about the user's behavior and transfers this knowledge to the network. The robot in the remote location accesses this knowledge and according to this information emulates the behavior of the remote user when interacting with its partner. The behavioral patterns are grouped into macro-behavior units (maBUs) and mirco-behavior units (miBUs). maBUs carry information that is specific to a person-to-person communication. miBUs are commonly used behavior patterns within a certain cultural environment (e.g. handshake, bow etc). maBUs are usually chains of miBUs. miBUs are chains of expression actions (e.g. gesture, facial expression etc.). The idea behind this is, that human communication contains several levels or layers of information exchange. This to be emulated by implementing the concept of miBUs and maBUs. We present a preliminary application of this concept to a musical context. The rhythmic motion of a drum-stick during the performance of a drum rhythm by a musician is recorded by a inertial measurements unit and transmitted between two far distance locations (Waseda University in Japan and Karlsruhe Institute of Technology in Germany) using three different transmission methods: direct raw data transmission, miBU based transmission and maBU-based transmission. We present experimental results that show quantitative data to evaluate the suitability of our approach, with the overall goal to implement a telepresence system of larger scale.

Personal robots and robot technology (RT)-based assistive devices are expected to play a major role in our elderly-dominated society, by interacting with surrounding people both physically and psychologically. A fundamental role during the interaction is of course played by the hand. In this paper we present the evaluation of the effect of hand shape to the quality of the interaction, in particular during handshake.

In recent years there has been an ever increasing amount of research and development of technologies and methods to improve the quality and the performance of advanced surgery. In other fields several training methods and metrics have been proposed, both to improve the surgeon's abilities and also to assess her/his skills. For neurosurgery, however, the extremely small movements and sizes involved have prevented until now the development of similar methodologies and systems. In this paper we present the development of an ultra-miniaturized Inertial Measurement Unit and its application for the evaluation of the performance in a simple pick and place scenario. This analysis is a preliminary yet fundamental step to realize a better training/evaluation system for neurosurgeons, and to objectively evaluate and understand how the neurosurgery is performed.

Personal robots and robot technology (RT)-based assistive devices are expected to play a major role in our elderly-dominated society, with an active participation to joint works and community life with humans, as partner and as friends for us. In particular, these robots are expected to be fundamental for helping and assisting elderly and disabled people during their activities of daily living (ADLs). To achieve this result, personal robots should be also capable of human-like emotion expressions. To this purpose we developed a new whole body emotion expressing bipedal humanoid robot, named KOBIAN, which is also capable to express human-like emotions. In this paper we presented three different evaluations of the emotional expressiveness of KOBIAN. In particular In particular, we presented the analysis of the roles of the face, the body, and their combination in emotional expressions. We also compared Emotional patterns created by a Photographer and a Cartoonist with the ones created by us. Overall, although the experimental results are not as good as we were expecting, we confirmed the robot can clearly express its emotions, and that very high recognition ratios are possible.

Personal robots and robot technology (RT)-based assistive devices are expected to play a major role in our elderly-dominated society, with an active participation to joint works and community life with humans, as partner and as friends for us. The authors think that the emotion expression of a robot is effective in joint activities of human and robot. In addition, we also think that bipedal walking is necessary to robots which are active in human living environment. But, there was no robot which has those functions. And, it is not clear what kinds of functions are effective actually. Therefore we developed a new bipedal walking robot which is capable to express emotions. In this paper, we present the design and the preliminary evaluation of the new head of the robot with only a small number of degrees of freedom for facial expression.

Minimally invasive surgery (MIS) has become very common in recent years, thanks to the many advantages it provides for patients. Since it is difficult for surgeons to learn and master this technique, several training methods and metrics have been proposed, both to improve the surgeon's abilities and also to assess his/her skills. This paper presents the use of the WB-1R (Waseda bioinstrumentation system no.1 refined), which was developed at Waseda University, Tokyo, to investigate and analyze a surgeon's movements and performance. Specifically, the system can measure the movements of the head, the arms, and the hands, as well as several physiological parameters. In this paper we present our experiment to evaluate a surgeon's ability to handle surgical instruments and his/her depth perception using a laparoscopic view. Our preliminary analysis of a subset of the acquired data (i.e. comfort of the subjects; the amount of time it took o complete each exercise; and respiration) clearly shows that the expert surgeon and the group of medical students perform very differently. Therefore, WB-1R (or, better, a newer version tailored specifically for use in the operating room) could provide important additional information to help assess the experience and performance of surgeons, thus leading to the development of a global performance index for surgeons during MIS. These analyses and modeling, moreover, are an important step towards the automatization and the robotic assistance of the surgical gesture.

Personal robots, which are expected to become popular in the future, are required to be active in joint work and community life with humans. Such robots must have no bad physical or psychical effect on humans. The psychical effect of a robot on humans has been subjectively measured using questionnaires. However, it has not been objectively measured yet. Human emotion and the consciousness direction can be measured by physiological parameters and body motion, respectively. Therefore, the bioinstrumentation system WB-1 was developed in order to objectively measure the psychical effect of a robot on a human. It can measure physiological parameters such as respiration, heart rate, perspiration and pulse wave, and arm motion. Analyzing human stress in the interaction with a robot from electrocardiogram, the robot could generate a motion for decreasing the stress

Personal robots, which are expected to become popular in the future, are required to be active in joint work and community life with humans. Therefore, we have been developing new mechanisms and functions for a humanoid robot that has the ability to express emotions and to communicate with humans in a human-like manner. In 2004, we introduced the "Behavior Model" and "Consciousness Model" to the robot mental model so that the robot generated various kinds of behavior and an object of the robot's behavior became clear. We implemented the mental model in the emotion expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II). Also, we have been studying a system of multiple harmonic oscillators (neurons) interacting via chaotic force since 2002. Each harmonic oscillator is driven by chaotic force whose bifurcation parameter is modulated by the position of the harmonic oscillator. In this paper, we propose an associative memory model using mutually coupled chaotic neural networks for generating an optimum behavior to a stimulus. We implemented this model in the emotional expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II).

The authors have been developing humanoid robots in order to develop new mechanisms and functions for a humanoid robot that has the ability to communicate naturally with a human by expressing human-like emotion. We considered that human hands play an important role in communication because human hands have grasping, sensing and emotional expression abilities. Then, we developed the emotion expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II) by integrating the new humanoid robot hands RCH-1 (RoboCasa Hand No.1) into the emotion expression humanoid robot WE-4R. Furthermore, we confirmed that RCH-1 and WE-4RII had effective emotional expression ability because the correct recognition rate of WE-4RII's emotional expressions was higher than the WE-4R's one. In this paper, we describe the mechanical features of WE-4RII.

Among social infrastructure technologies, robot technology (RT) is expected to play an important role in solving the problems of both decrease of birth rate and increase of elderly people in the 21st century, specially but not only in Japan. In order to achieve this objective, the new generation of personal robots should be capable of a natural communication with humans by expressing human-like emotion. In this sense, human hands play a fundamental role in communication, because they have grasping, sensing and emotional expression ability. This paper presents the recent results of the collaboration between the Takanishi Lab of Waseda University, Tokyo, Japan, and the Arts Lab of Scuola Superiore Sant'Anna, Pisa, Italy, and ROBOCASA. In this paper, the development of a novel anthropomorphic hand for humanoid robotics RCH-1 (ROBOCASA Hand No.1) and its integration into a humanoid robotic platform, named WE-4RII (Waseda Eye No.4 Refined II) is presented.

This paper presents an underactuated artificial hand intended for functional replacement of the natural hand in upper limb amputees. The natural hand has three basic functionalities: grasping, manipulation and exploration. To accomplish the goal of restoring these capabilities by implanting an artificial hand, two fundamental steps are necessary: to develop an artificial hand equipped with artificial proprioceptive and exteroceptive sensors and to fabricate an appropriate interface able to exchange sensory-motor signals with the amputee's body and the central nervous system. In order to address these objectives, we have studied an underactuated hand according to a biomimetic approach, and we have exploited robotic and microengineering technologies to design and fabricate its building blocks. The architecture of the hand comprises the following modules: an actuator system embedded in the underactuated mechanical structure (artificial musculoskeletal system), a proprioceptive sensory system (position and force sensors), an exteroceptive sensory system (3D force sensors distributed on the cosmetic glove), an embedded control unit, and a human/machine interface. The first prototype of the artificial hand has been designed and fabricated. The hand is underactuated, and is equipped with opposable thumb and a proprioceptive sensory system. This paper presents the fabrication and experimental characterization of the hand, focusing on the mechanical structure, the actuator system and the proprioceptive sensory system.

The objective of the project described in this paper is the development of a cybernetic prosthesis, replicating as much as possible the sensory-motor capabilities of the natural hand. The human hand is not only an effective tool but also an ideal instrument to acquire information from the external environment. The development of a truly human-like artificial hand is probably the most widely known paradigm of "bionics". The Cyberhand Project aims to obtain a cybernetic prosthetic hand interfaced to the peripheral nervous system. In particular this paper is focused on the hand mechanisms design and it presents preliminary results in developing the three fingered anthropomorphic hand prototype and its sensory system.

The field of humanoids robotics is widely recognized as the current challenge for robotics research. Developing humanoids poses fascinating problems in the realization of manipulation capability, which is still one of most complex problem in robotics. The paper, starting from an overview of current activities in the development of humanoid robots, with special focus on manipulation, presents the authors' approach to the design and development of anthropomorphic sensorized hands and of anthropomorphic control and sensory-motor coordination schemes. Current achievements at the Scuola Superiore Sant'Anna and Centro INAIL RTR (Research Centre on Rehabilitation Bioengineering) in the development of a robotic human prosthesis are described, together with preliminary experimental results, as well as in the implementation of biologically-inspired schemes for control and sensory-motor co-ordination, derived from models of well-identified human brain areas.