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Neuromotor training program are recommended as part of essential activity programs for older adults. With the growth of wearable sensor technology, wearable sensor provides a low-cost monitoring method for objective exercise assessment. Customized remote sensors combination with off-the-shelf smart phone provides a high performance and low-cost monitoring platform. A connection-oriented sensor network with Bluetooth Low Energy (BLE) provides high bandwidth encrypted communication. With multiple remotes sensors, synchronization between sensors is fundamental. However, the accuracy with the generic BLE time service is limited. In this paper, we present a novel method that can potentially synchronize multiple sensors with an unmodified Android Device. The method is based on timestamping the Connection Event (Anchor Point) on the Slave side. The results show an absolute error is below 1 ms across two sensors, which is ideal for motion sensing.

Resistance bands are often used in resistance training programs for older adults. Despite their widespread use, there is a lack of objective assessment of the actual strength, speed and precision of the movements during these exercises. Therefore, this paper presents the development of a sensorised resistance-band and a preliminary trial of activities classification by using artificial intelligence. The results show that in the preliminary trial, the classification accuracy of 4 different activities reached over 96% using accelerometer data only. A future study will be based on the sensorised resistance band to quantify resistance band exercises objectively in elderly people.

BackgroundUnfortunately, global efforts to promote “how much” physical activity people should be undertaking have been largely unsuccessful. Given the difficulty of achieving a sustained lifestyle behavior change, many scientists are reexamining their approaches. One such approach is to focus on understanding the context of the lifestyle behavior (ie, where, when, and with whom) with a view to identifying promising intervention targets. ObjectiveThe aim of this study was to develop and implement an innovative algorithm to determine “where” physical activity occurs using proximity sensors coupled with a widely used physical activity monitor. MethodsA total of 19 Bluetooth beacons were placed in fixed locations within a multilevel, mixed-use building. In addition, 4 receiver-mode sensors were fitted to the wrists of a roving technician who moved throughout the building. The experiment was divided into 4 trials with different walking speeds and dwelling times. The data were analyzed using an original and innovative algorithm based on graph generation and Bayesian filters. ResultsLinear regression models revealed significant correlations between beacon-derived location and ground-truth tracking time, with intraclass correlations suggesting a high goodness of fit (R2=.9780). The algorithm reliably predicted indoor location, and the robustness of the algorithm improved with a longer dwelling time (>100 s; error

Poor balance control and falls are big issues for older adults that due to aging decline have a lower postural balance and directional control in balance performance than younger age groups. The four square step test (FSST) was developed to evaluate rapid stepping that is often required when changing direction and avoiding obstacles while walking. However, previous researchers used only the total time as the assessment in the test. The aim of this letter is to objectively quantify the sequence and direction of the steps in FSST, by using two inertial sensors placed on both feet. An algorithm was developed to automatically segment the steps performed during the test, and calculate the stepping direction from the linear velocity of the foot. Experiments were conducted with 100 Japanese healthy older adults, where sensor data and video of 20 subjects were randomly subtracted for algorithm verification. The results showed that the algorithm succeeded for 71.7% trials in recognizing both the step sequence and step direction in FSST, while 90.2% of the detection failure could be excluded with an auto verification method.

The commercially available Perception Neuron motion capture (Mo-Cap) system is a cost effective and easy to use option for motion analysis. However, the accuracy of this system in a practical setting is unknown and needs to be evaluated if it is to be considered for applications that require a specific level of measurement precision. Therefore, the validity of the Mo-Cap system for estimating postural angular kinematics of the upper body was assessed. Upper body motion was evaluated through three-dimensional analysis of functional movements performed by the neck, thorax and shoulders. Range of motion (RoM) estimates were compared to Vicon using Bland-Altman analysis. Systematic biases in neutral to peak RoM differences were all ≤4.5° and random biases ≤±4.5° except for neck extension where the values were larger. The present findings suggest that the Mo-Cap system is a valid method for assessing the majority of upper body ROM to within 5°.

Nowadays, with the development of the proportion of the elderly population in the world, several problems caused by the population aging gradually into people's horizons. One of the biggest problems plagued the vast majority of the elderly is hemiplegia, which leads to the vigorous development of the physical therapists. However, these traditional methods of physical therapy mainly rely on the skill of the physical therapists. In order to make up the defects of traditional methods, many research groups have developed different kinds of robots for lower limb rehabilitation training but most of them can only realize passive training which cannot adopt rehabilitation training based on the patients' individual condition effectively and they do not have a rehabilitation evaluation system to assess the real time training condition of the hemiplegic patients effectively. In order to solve the problems above, this paper proposed a lower limb rehabilitation evaluation system which is based on the virtual reality technology. This system has an easy observation of the human-computer interaction interface and the doctor is able to adjust the rehabilitation training direct at different patients in different rehabilitation stage based on this lower limb rehabilitation evaluation system. Compared with current techniques, this novel lower limb rehabilitation evaluation system is expected to have significant impacts in medical rehabilitation robot field.

Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. The needs for hemiplegic rehabilitation is increasing quickly. As traditional rehabilitation, each patient must be treated by therapist, one by one. However, because of the different levels of therapists, the rehabilitation cannot be performed as the as the same. Normally, the rehabilitation status diagnosing is still be performed by therapists with the subjective experience. It caused the inhomogeneity on rehabilitation evaluation. It also sometimes causes negative influence on the rehabilitation effect. To solve these problems, many researches focusing on assessing the status of the hemiplegic patients quantitatively are proposed rehabilitation evaluation systems. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. In this paper, a method is presented to detect lower limb motion of hemiplegic patients based on inertial sensor technology. The gesture quaternion of lower limb can be obtained through LPMS. With the matrix and Euler angle changing algorithm, combining with the simplified lower limb motion model, the rotation angle of joint can be computed. Finally, the curve of rotation angle of knee is established.

In gait rehabilitation, achieving a gait analysis method using a simple system during long-distance walking is important. This method is required to measure all gait parameters in a single measurement. In addition, it is required that the measurement system is not spatially constrained. Therefore, we have been developing a gait tracking system with acceleration sensors for long-distance gait rehabilitation. In this paper, we describe a gait phase detection method using foot acceleration data for estimating ground reaction force during long-distance gait rehabilitation. To develop this method, we focused on the jerk of each foot in vertical axis direction. Using two accelerometers mounted on the left and right feet, we carried out three experiments. First, we measured the jerk of each foot during a free gait to verify the relation with the walking speed. Second, we measured the jerk of each foot during walking faster than normal for each subject. We then compared these results with the results of first experiments. Finally, we measured the jerk of each foot during left-right asymmetrical walking. The results confirmed that gait phase could be detected using the jerk of each leg, calculated from acceleration data in vertical axis direction. In particular, the timing of Heel-contact / Toe-off could be obtained with an average error of 0.03 s. And as a preliminary study, we estimated the ground reaction force using the one of the results.

Problem statement: Jaw movement analysis, as a clinical aid, can prov ide an objective basis for understanding and diagnosing jaw musculos keletal disorders. Therefore, the use and development of devices for quantitatively measuring and analyzing jaw movement have become more common and popular in the clinic. Many types of jaw tracking devices have been developed, but most of them are still not handy and easy to be used. Approach: To improve the handiness and utility of the jaw movement analysis devices, we developed a simple to be used jaw tracking prototype by using a new ultra-miniaturized Inertial Measurement Unit (I MU) named WB-3. The WB-3 IMU was composed by 3-axis gyroscope, 3-axis accelerometer and 3-aixs magnetometer, which can not only measure the acceleration and angular speed of jaw movement, but also can measure mouth opening angle. The IMU's extremely reduced weight and size allowed it to be easily adhered to mandible during normal tests without physical restriction to the subjects. A preliminary experiment for jaw movement analysis during free chewing of three types of food with different shapes and hardness was evaluated. A group of 15 healthy subjects aged from 21-36 years old kindly participated in the experiment. Results: The parameters of chewing time, chewing frequency, power spectrum density of jaw's angular speed and acceleration, cumulative di stribution function of jaw's acceleration and mouth opening angle were presented. The experimental results clearly showed that the subjects used less chewing time, less chewing frequency, less accelera tion cumulative distribution and energy to eat soft food; higher values were found in the case of hard food and there was no significant difference in mouth opening angle while eating these three foods. Conclusion: Our jaw movement analysis prototype using IMU WB-3 was proved to be a valid and handy method for jaw movement and pattern analysis which may be used clinically as an assista nt system for dental therapy.

Robots, especially humanoids, are expected to perform human-like actions and adapt to our ways of communication in order to facilitate their acceptance in human society. Among humans, rules of communication change depending on background culture: greetings are a part of communication in which cultural differences are strong. Robots should adapt to these specific differences in order to communicate effectively, being able to select the appropriate manner of greeting for different cultures depending on the social context. In this paper, we present the modelling of social factors that influence greeting choice, and the resulting novel culture-dependent greeting gesture and words selection system. An experiment with German participants was run using the humanoid robot ARMAR-IIIb. Thanks to this system, the robot, after interacting with Germans, can perform greeting gestures appropriate to German culture in addition to a repertoire of greetings appropriate to Japanese culture.

Current prosthetic hands are basically simple grippers with one or two degrees of freedom, which barely restore the capability of the thumb-index pinch. Although most amputees consider this performance as acceptable for usual tasks, there is ample room for improvement by exploiting recent progresses in mechatronics design and technology. We are developing a novel prosthetic hand featured by multiple degrees of freedom, tactile sensing capabilities, and distributed control. Our main goal is to pursue an integrated design approach in order to fulfill critical requirements such as cosmetics, controllability, low weight, low energy consumption and noiselessness. This approach can be synthesized by the definition "biomechatronic design", which means developing mechatronic systems inspired by living beings and able to work harmoniously with them.This paper describes the first implementation of one single finger of a future biomechatronic hand. The finger has a modular design, which allows to obtain hands with different degrees of freedom and grasping capabilities. Current developments include the implementation of a hand comprising three fingers (opposing thumb, index and middle) and an embedded controller.

The use of inertial sensors for the gait event detection during a long-distance walking, for example, on different surfaces and with different walking patterns, is important to evaluate the human locomotion. Previous studies demonstrated that gyroscopes on the shank or foot are more reliable than accelerometers and magnetometers for the event detection in case of normal walking. However, these studies did not link the events with the temporal parameters used in the clinical practice; furthermore, they did not clearly verify the optimal position for the sensors depending on walking patterns and surface conditions. The event detection quality of the sensors is compared with video, used as ground truth, according to the parameters proposed by the Gait and Clinical Movement Analysis Society. Additionally, the performance of the sensor on the foot is compared with the one on the shank. The comparison is performed considering both normal walking and deviations to the walking pattern, on different ground surfaces and with or without constraints on movements. The preliminary results show that the proposed methodology allows reliable detection of gait events, even in case of abnormal footfall and in slipping surface conditions, and that the optimal location to place the sensors is the shank.

Cranial nerve examination takes an important role in the physical examination. All the medical staffs need to be trained to master the skills for examination. By now, several training methods have been carried out for medical training including training with the simulated patient (SP). However, considering the characters of eyeball, the involuntary actions cannot be simulated by Sp. With the developments of technology, more and more robot heads have been launched. However, these simulators only focus on mimicking the healthy human abilities, not simulating disorders for medical training. In this paper, we propose a novel eyeball motion nerve model which is used in the head robot named WKH-2(Waseda Kyotokagaku Head Robot No.2). This robot is designed to simulate the disorders of eyeball movements to give the trainee a full training on cranial examination. The motor nerve model is carried out from mimicking the real eyeball nerve structure. And the functions of each part are designed from analysis of the real functions of each organ. In this robot, the effects of eyeball motion nerve system, and various symptoms are simulated. Making use of this robot, a systematic training on the skills as well as the understanding of medical knowledge is provided. Finally, several experiments are carried out to verify our proposed system. The experimental results show that the approach is worth following in further research.

A tightly-coupled stereo vision-aided inertial navigation system is proposed in this work, as a synergistic incorporation of vision with other sensors. In order to avoid loss of information possibly resulting by visual preprocessing, a set of feature-based motion sensors and an inertial measurement unit are directly fused together to estimate the vehicle state. Two alternative feature-based observation models are considered within the proposed fusion architecture. The first model uses the trifocal tensor to propagate feature points by homography, so as to express geometric constraints among three consecutive scenes. The second one is derived by using a rigid body motion model applied to three-dimensional (3D) reconstructed feature points. A kinematic model accounts for the vehicle motion, and a Sigma-Point Kalman filter is used to achieve a robust state estimation in the presence of non-linearities. The proposed formulation is derived for a general platform-independent 3D problem, and it is tested and dem...

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.

A device for the gait analysis during a long-distance walking is important for the correct assessment of patients during the rehabilitation. This device should be able to measure all gait parameters in a single unit. In addition, it is required that the measurement system is not spatially constrained. In our group, we have been developing a new wireless system, namely WB-4R, composed of Inertial Measurement Units, to be used in rehabilitation centers for gait analysis that is cheap, small, and relatively maintenance-free. This paper presents the results of a pilot study conducted with healthy subjects. The system was able to detect the gait phase and provide frequency analysis of the angular velocity and acceleration of the lower limbs.

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.

In the era of globalization and standardization, in the perspective of industrial system integration, the implementation of a network framework able to interconnect any type of device and supporting both real-time (RT) and time-uncritical communication is becoming a must. This paper proposes an original entirely software-based communication framework to support RT communication over standard Ethernet, and compares it with the most relevant commercially available RT protocols in term of global costs and performances.

Personal robots and Robot Technology (RT)-based assistive devices are expected to play a substantial role in our society, largely populated by elders; they will play an active role in joint works and community life with humans. In particular, these robots are expected to play an important role for the assistance of elderly and disabled people during normal activities of daily living (ADLs). To achieve this result, personal robots should be also capable of human-like emotion expressions. In this perspective we developed a whole body bipedal humanoid robot, named KOBIAN, which is also capable to express human-like emotions. In this paper we present the mechanical and modular design of KOBAIN.

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 methodologies aimed at improving the safety of advanced surgery. In this context, several training methods and metrics have been proposed, in particular for laparoscopy, 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 the ultra-miniaturized Inertial Measurement Unit WB3 (at present the smallest, lightest, and best performing in the world) for practical application in neurosurgery as skill assessment tool. This paper presents the feasibility study for quantitative discrimination of movements of experienced surgeons and beginners in a simple pick and place scenario.

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 capable of human-like emotion expressions; in addition, human-like bipedal walking is the best solution for the robots which should be active in the human living environment. Although several bipedal robots and several emotional expression robots have been developed in the recent years, until now there was no robot which integrated all these functions. Therefore we developed a new bipedal walking robot, named KOBIAN, which is also capable to express human-like emotions. In this paper, we present the design and the preliminary evaluation of the new emotional expression head. The preliminary results showed that the emotion expressed by only the head cannot be really easily understood by the users. However, the presence of a full body clearly enhances the emotion expression capability of the robot, thus proving the effectiveness of the proposed approach.

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 near future, are required to be active in work and community life alongside humans. Therefore, we have been developing new mechanisms and functions in order to realize natural bilateral interaction by expressing emotions, behaviors and personality in a human-like manner. We have proposed a mental model with emotion, mood, personality and needs. However, the robot behavior was very simple since the robot shows just a single kind of behavior in response to a robot mental state. In this paper, we present a new behavior model for humanoid robots based on operant conditioning, which is a well-known psychological behavior model. We implemented this new behavior model into the emotion expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II), developed in 2004. Through the experimental evaluations, we confirmed that the robot with the new behavior model could autonomously select suitable behavior for the situation within a predefined behavior list

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.

The aim of this paper is to discuss an ideal design procedure for biologically-inspired mechano-sensors. The main steps of this procedure are the following: (1) analysis of force and position sensors in humans; (2) analysis of technologies available for MEMS (Micro Electro Mechanical Systems) and (3) design and implementation of biologically-inspired sensors in innovative mechatronic and biomechatronic systems (e.g., anthropomorphic robots, prostheses, and neuroprostheses).

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. In 2004, we developed the emotion expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II) by integrating the new humanoid robot hands RCH-I (RoboCasa Hand No.1) into the emotion expression humanoid robot WE-4R. We confirmed that WE-4RII can effectively express its emotion.

In a society getting older year by year, Robot technology (RT) is expected to play an important role. 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, the 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 a biologically-inspired approach for the development of a new humanoid hand. In particular, the grasping and gestural capabilities of the novel anthropomorphic hand for humanoid robotics RCH-1 (RoboCasa Hand No.1) are presented.

WABIAN-2R is a bipedal humanoid robot which is capable of stretched knee walking with heel-contact and toe-off motions due to the presence of a 2-DoF waist and a passive joint for bending toe motion, and can thus mimic human-like walking. This paper aims to determine the similarity between the walking gait of WABIAN-2R to the natural walking gait of a human of comparable size and stature, on the factors (i) pelvic tilt, (ii) pelvic rotation, (iii) swing and stance percentage, and (iv) double limb support and single limb support percentage using inertial measurement units and force-torque sensors.

A Personal Robot is expected to become popular in the future. It is 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 can express emotions and communicate naturally with humans. In this paper, we present the mechanical design of the Emotion Expression Humanoid Robot WE-4RII, which was developed by integrating the Humanoid Robot Hands RCH-1 into the previous version WE-4R. The robot has four of the five human senses for detecting external stimuli: visual, tactile, auditory and olfactory, and 59-DOFs for expressing motion and emotions. It is capable of expressing seven basic emotional patterns.

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 where the average age of the population is rising faster than any other nation in the world. 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 exploration, communication and interaction with objects and other persons. This paper presents the recent results of the collaboration between the Takanishi Lab of Waseda University, Tokyo, Japan, the Arts Lab of Scuola Superiore Sant'Anna, Pisa, Italy, and ROBOCASA, Tokyo, Japan. At first, the integration of the artificial hand RTR-2 of ARTS lab with the humanoid robotic platform WE-4R during ROBODEX2003 is presented. Then, the paper show the preliminary results of the development of a novel anthropomorphic hand for humanoid robotics RCH-I (ROBOCASA Hand No.1) and its integration into a new humanoid robotic platform, named WE-4RII (Waseda Eye No.4 Refined II).