Unmanned aerial vehicles (UAVs) are used in many industrial fields and human–drone interaction (HDI) has seen increasing research attention in recent years. Their ability to fly divides UAVs from other robots and novel social robots are expected to be developed from UAVs in the future. However, touch interaction is critical in social robotics, and ordinary UAVs tend to be unsafe to touch. Furthermore, studies on whole-body interaction between drones and humans, including dancing, are far less common than those with traditional robots. Therefore, we developed “Soft Flying Robot,” a new type of flying robot for HDI research. Its flight uses helium gas and piezoelectric air pumps, making it blade-free and safe for humans to touch and interact with. In addition, it is equipped with touch sensors and light-emitting units to enable clearer and more immersive interaction. We evaluated Soft Flying Robot by introducing it to a group of performers, observing them use it in a dance workshop, and asking them for their impressions. Initial results indicate that Soft Flying Robot induces new behaviors in users and draws visual attention. This paper mainly discusses the results of the qualitative analysis of Soft Flying Robot’s potential in human–drone co-creation.

Wrist rehabilitation robotic devices have delivered the repetitive and gradual training necessary to rehabilitate individuals with wrist impairments properly. Generally, there are two approaches for the design of the wrist rehabilitation devices. In one approach, the motors are placed on the forearm with complex transmission mechanisms to reduce the weight and inertia. In the other approach, rotary motors are placed close to the wrist joints with simple design, and this leads to high weight and inertia. In this paper, a simple design of two-degrees of freedom compliant and balanced wrist rehabilitation device is proposed. It can provide the radial-ulnar deviation and flexion-extension rehabilitation motions. In the proposed design, the servomotors that are placed close to the wrist joints are counterweight balanced to reduce the inertia and the required torques. The balancing is carried out by optimizing the center of mass of the device in the SolidWorks model. A custom design series elastic unit is proposed to be coupled to the servomotor to achieve the compliance for safe human-robot interaction. Based on the device dynamics modeled by ADAMS software, hybrid position and force tracking impedance control is developed for position and force tracking through the different therapeutic exercises. The device is shown to be capable of achieving the different therapeutic exercises compliantly such as the passive, active-assisted and isometric exercises.

In recent years, awareness of improving the quality of medical care has increased. We focused on neonatal resuscitation, which is difficult to train clinically, and our long-term goal is a neonatal resuscitation training system that can simulate cases and can feedback interactively based on quantitative evaluation of the procedures. In this study, we developed the neonatal simulator that has a respiratory movement simulating mechanism and a chest compression measurement mechanism. Through an interview with neonatologists, the fidelity of respiratory movements and the possibility of evaluating chest compression with the developed simulator were assessed.

For a small-sized biomimetic robot, it is challenging to mimic animal-like motion with high speed and high flexibility. To enable high flexibility, high stability, and high biomimicry degree for the robotic rat, we drew inspirations from three agile rat movements, namely, the pitch, yaw, and U-turn movements. First, we proposed key movement joints (KMJs) to capture a decent representation of the rat with a reduced-order model. By extracting the primary KMJs, we determined the number and distribution of robotic joints for the design of a bioinspired spine mechanism. Second, to meet the demand of high biomimicry degree, we generated an optimal compensation term to minimize the trajectory error introduced by simplifying the model. Moreover, we calculated the optimal minimum motion cycle based on the constraints of equilibrium under extreme conditions to ensure high flexibility without compromising the stability. Finally, the proposed method was successfully verified through simulation and experimental tests with a robotic rat endowed with the bioinspired spine mechanism.

Social interaction between a robot and rats is important since the robot can generate reproducible social behaviors across trials. However, lacking internal state feedback from the rat makes current robot-rat interaction a very preliminary level comparing with rat-rat interaction. Previous biological studies showed that ultrasonic vocalizations (USVs) emitted by a rat are expressions of its internal emotional states, which therefore can be used as part of feedback for a robot-rat interaction. The challenge is to accurately identify rat USVs in real-time from mix sounds generated by the robot in a noisy environment. To address these problems, we propose an SVM-based rat USVs identification method. This SVM method uses three types of features to represents the characteristics of mix sound and use these multidimensional features to identify rat USVs. Results show that our identification method has an accuracy of 84.29% with only 4.84% false-positive rate. Furthermore, we carefully design the filter window length with respect to sound chunk length and use only one microphone to record the mix sound. All of these efforts are to reduce the calculation time to realize real-time identification. Eventually, the identification process can be executed within 3. 5ms, which definitely meet the real-time demand. This research lays the foundation of the feedback based interaction between rat and robot, and also shows promise in the study of ethology and the interaction between robot and animals.

The main goal of robot swarm is to maintain formation among their members while avoiding obstacles and tracking a target in the surrounding environment. One popular approach for achieving this goal is the Potential Field Method (PFM). Thus, in this paper, we propose a formation control algorithm based on the PFM and Fuzzy Inference System (FIS). The Proposed PFM is intended to maintain formation, avoid obstacles and track a moving target as well. We add an interaction potential force to maintain formation beside the attractive and repulsive potential forces. Also, we use the FIS to adapt the change of the relative distances among robots in the swam and other entities int he environment. To test the scalability and reliability of the proposed formation control algorithm, simulations of robot swarms using MATLAB software with a different number of robots following different target trajectories in different environment setups are recorded. Results confirm the efficiency and the applicability the proposed formation control algorithm in achieving the three tasks of the robot swarm.

Effects of the subthreshold slope of transistor switching on the sensitivity of the square law detector composed of a high electron mobility transistor (HEMT) to detect terahertz waves have been investigated. Theoretical analysis starting from the unified charge control model of channel carriers has been carried out, which comes down to mathematical formulae suggesting that the subthreshold slope significantly affects the output voltage and the sensitivity of the square law detector. Square law detectors have been fabricated using HEMT with a MOS structured gate on glass substrate to detect 1.0 THz waves. HEMT was composed of InGaAs/InAs/InGaAs double hetero-structured channel. Detection tests using the MOS-HEMT square law detector have clearly shown that the output voltage increases with the subthreshold slope.

The interaction test between a robotic rat and living rat is considered as a possible way to quantitatively characterize the rat sociality. In such robot-rat interactions, the robot should be designed to fully replicate a real rat in terms of morphological and behavioral characteristics. To address this problem, a multi-jointed robot prototype has been modified based on our previous work. We optimally update the forelimb of the robot and redesign the control board to make it more dexterous and increase its behavioral capability. Then, we systematically and kinematically analyze the rotational range of joint variables and the workspace of the robot by using traversal method. To evaluate the motion capability of the modified robot, we propose two quantitative parameters: maximum reachable height (MRH) and minimum bendable distance (MBD). Additionally, we achieve to quantitatively evaluate the behavioral similarity between the robot and rat with the calculated accumulative distance (AD) by using dynamic time warping (DTW). These evaluated methods show high promise to improve the robot-rat interaction to be more similar to rat-rat interaction.

We developed a four-arm four-crawler advanced disaster response robot called OCTOPUS. Disaster response robots are expected to be capable of both mobility, e.g., entering narrow spaces over very rough unstable ground, and workability, e.g., conducting complex debris-demolition work. However, conventional disaster response robots are specialized in either mobility or workability. Moreover, strategies to independently enhance the capability of crawlers for mobility and arms for workability will increase the robot size and weight. To balance environmental applicability with the mobility and workability, OCTOPUS is equipped with a mutual complementary strategy between its arms and crawlers. The four arms conduct complex tasks while ensuring stabilization when climbing steps. The four crawlers translate rough terrain while avoiding toppling over when conducting demolition work. OCTOPUS is hydraulic driven and teleoperated by two operators. To evaluate the performance of OCTOPUS, we conducted preliminary experiments involving climbing high steps and removing attached objects by using the four arms. The results showed that OCTOPUS completed the two tasks by adequately coordinating its four arms and four crawlers and improvement in operability needs.

Small cell is an attractive and promising technology for improving capacity in traffic hotspots using cell densification. We consider the traffic load-balancing problem for a macro-assisted small cell architecture exploiting the flexible 3-D beamforming facilitated by the adoption of the active antenna system at base stations. Specifically, 3-D user equipment (UE)-specific beamforming is utilized for traffic load balancing due to its unique feature that the received signal is maximized, while the interference is limited with narrower beamwidth. We propose a novel traffic load-balancing algorithm based on cell association and cell sectorization using 3-D UE-specific beamforming, and the performance of the proposed algorithm is evaluated via system-level simulations. Results show that cell edge user throughput and cell average throughput both improve significantly with the proposed load-balancing algorithm compared with the conventional sectorization with fixed antenna down-tilt scheme. In addition, in denser small cell scenarios, our proposed scheme can further increase the load-balancing gain with reduced cell planning efforts compared with the conventional scheme.

Environment recognition is an effective way for a mobile robot to move across rough terrain. In particular, this makes it possible to prevent a tiny mobile robot from getting stuck or turning over. Several studies have been conducted on environment recognition using a laser range finder or camera. However, almost all of these studies focused on obstacle detection or shape recognition, which cannot be used to recognize the surface condition such as slipperiness. The purpose of this work is to design a model for estimating the surface condition using a tiny mobile robot. We set slipperiness as one of the parameters for recognizing the surface condition, which is already used by terramechanics, along with two additional parameters, the hardness and unevenness. We find that a robot can roughly estimate the ground hardness by measuring the current peak of a motor and the unevenness from measuring the robot posture. By recognizing the surface condition, the robot can change the parameters of the controlling motor based on the ground characteristics. This new method for recognizing the surface condition is significant, not only because it fills gaps in the previous research, but also because it does not require any special sensors such as a laser range finder and does not consume a large quantity of energy. Therefore, it achieves a core objective of our environmental monitoring system using multiple mobile robot.

Robots are possible candidates for performing tasks as helpers in activities of daily living in the future: working as a receptionist is one possible employment. However, the way the receptionist robot should appear, sound and behave needs to be investigated carefully, in order to design a robot which is accepted and perceived in a positive way by common users. This paper describes a study on anthropomorphism of a receptionist robot made for Brazilian people depending on the appearance and on the voice of the receptionist. This experiment was preceded by a preliminary survey about expectation of people regarding receptionists. The main experiment consisted in having Brazilian people interacting with a conversational agent and with a humanoid robot through a video conference. The two receptionists are not only different in physical appearance, but in the sound of the voice, too, which can be either human-like or robotic sound. The two receptionists gave indications to the participants to reach rooms where they could evaluate the receptionists through questionnaires concerning anthropomorphism and uncanniness among other concepts. The results gathered from both experiments provide useful hints to design a receptionist robot.

Dynamic allocation of subframes to uplink (UL) or downlink (DL) in time division duplex (TDD), termed `Dynamic TDD,' has been studied by the 3rd Generation Partnership Project (3GPP) since the Long Term Evolution (LTE) Release 11 timeframe. At the same time, 3GPP is also standardizing macrocell-assisted small cell heterogeneous architectures for inclusion in LTE Release 12 as a solution offering high data rate to user terminals (UEs) along with high system capacity through spatial reuse of spectrum. In this paper, we focus on a particular small cell architecture proposed by DOCOMO, known as the Phantom Cell architecture, which provides the option to support dynamic TDD. For an arbitrarily-located UE in a small cell network, we apply results from stochastic geometry to derive expressions for the distribution of DL signal to interference plus noise ratio (SINR) at an arbitrary UE and the distribution of UL SINR at its serving base station (BS). The analytical results are verified by system level simulations. These results can be used to study aspects of system design for small cells, and the sensitivity of SINR to the extent of synchronization across small cells employing dynamic TDD. In order to deal with the severe inter-cell interference (ICI) problem in dynamic TDD, we further propose a frequency domain interference coordination technique. Finally, system level simulations based on more realistic system models and assumptions are conducted to evaluate the performance of dynamic TDD systems and the proposed interference coordination technique.

Small cell is an attractive and promising technology for improving capacity in traffic hotspots using cell densification. In this paper, we propose the capacity enhancement for small cells under macrocell-assisted architecture utilizing the flexible 3-dimensional (3D) beamforming facilitated by the adoption of the active antenna system (AAS) at base stations (BSs). In contrast to conventional macrocell network, more dynamic and flexible 3D beamforming with narrow beamwidth is feasible in the small cell layer because the service coverage and mobility robustness are basically supported in the macrocell layer. This dynamic beam adaptation in full dimensions can improve the received signal quality and at the same time control the interference more effectively, which is especially useful for the dense small cell deployment scenario where the interference issue is one of the major concerns. In particular, performance comparison between the conventional sectorization with fixed down-tilt scheme and UE (user equipment)-specific 3D beamforming is studied. Furthermore, a novel UE group-specific 3D beamforming is proposed as a more realistic operation compared to UE-specific beamforming. System level simulations demonstrate the significant gain of capacity enhancement with 3D beamforming over the conventional sectorization with fixed down-tilt in terms of both the cell average capacity (up to 124.8% gain) and the cell edge user throughput (up to 454.3% gain). It is also shown that UE group-specific beamforming can achieve performance comparable to that of UE-specific beamforming.

In the past we achieved to use a rat-like robot and a single rat to develop Animal Models of Mental Disorder (AMMDs) through stress exposure. However, to simulate the real social environment, we use a rat-like robot composed of multiple links to chase a specific rat (target) in a group of rats (outside observers). In this paper, we aim to develop a real-time control system for a multi-link robot surrounded by multiple rats. A virtual impedance model was adopted to generate posture and trajectory for a multi-link robot named WR-5. With the analysis of virtual forces/moments acting on WR-5 based on the model, corresponding dynamic equations can be obtained to control the motion of WR-5. Simulation results show that the head of WR-5 can accurately direct a target object in the following test. After conducting experiments with three rat subjects (a target rat, two outside observers), the output results suggest that the head and body gesture of WR-5 achieves to follow the target in real-time. Meanwhile, the control system allows real-time avoidance of the moving outside observers during interaction.

Macrocell-assisted small cell concepts, such as "Phantom cell concept" and "soft cell concept", have been proposed previously for interference management, flexible cell planning, and energy saving in dense small cell deployments. These concepts require macrocell involvement to improve links between small cell and user. Since target implementation areas of the concepts are crowded urban areas (e.g. downtown New York City) to satisfy the data need, more realistic simulations are needed to be implemented compared to conventional evaluations. In this paper, as a new approach to urban area LTE simulations, Manhattan grid layout is presented and implemented for mobility performance of Macrocell-assisted small Cell concept. The results show that the macrocell involvement to improve mobility performance gives a great advantage compared to using the conventional mobility solution for dense small cell deployments.

Small cell is an attractive and promising technology for improving capacity in traffic hotspots using cell densification. We consider the traffic load balancing problem for small cells under the enhanced Local Area (eLA) architecture utilizing the flexible 3-dimensional (3D) beamforming facilitated by the adoption of the active antenna system (AAS) at base stations (BSs). Different load balancing methods based on combinations of cell association algorithms and antenna tilt adjustment schemes are proposed and evaluated via system level simulations. Results show the potential gain of traffic load balancing with 3D beamforming in terms of cell edge user throughput. In particular, for the enhanced load balancing cell association combined with UE (user equipment)-specific tilting scheme, significant cell edge user throughput improvements can be achieved while good average cell throughput performance can still be maintained.

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 Third Generation Partnership Project (3GPP) has been studying dynamic allocation of sub-frames to uplink or downlink in Time Division Duplex (TDD), since the Long Term Evolution (LTE) Rel. 11 timeframe. At the same time, 3GPP is also standardizing Enhanced Local Area (eLA) small-cell heterogeneous architectures for inclusion in 3GPP Rel. 12 as a solution offering high data rate to user terminals (UEs) along with high spatial reuse of spectrum. In this paper, we focus on a particular eLA architecture proposed by DOCOMO, called the Phantom Cell architecture, that has the option to support dynamic TDD. We evaluate the system performance of dynamic TDD in phantom cells and the corresponding inter-cell interference issues. Then we propose a frequency domain interference coordination technique for dynamic TDD in phantom cells. The superior performance of the proposed scheme over conventional frequency reuse technique and no interference coordination scenario is verified by system level simulations.

The Third Generation Partnership Project (3GPP) is presently standardizing Enhanced Local Area (eLA) small-cell heterogeneous architectures for inclusion in Long Term Evolution (LTE) Release 12 as a solution offering high data rate to user terminals (UEs) along with high system capacity through spatial reuse of spectrum. At the same time, Energy Efficiency (EE) is becoming an important metric in evaluating the next generation of small cell networks. In this paper, we focus on a particular eLA architecture proposed by DOCOMO, called the Phantom Cell architecture. We use results from stochastic geometry to compare the EE of the phantom cell architecture versus the baseline small cell network, defined as a conventional frequency division duplex (FDD) LTE pico-cell deployment that uses the same spectrum as the underlying macrocellular network.

This paper proposes the use of a specific mathematical model to represent the relationship between rat behavior and sociality (degree of friendliness with the robot) in the robot-rat interaction system. To validate the model, we conducted social interaction test between a rat-like robot and real, live rats. A rat-like robot called WR-4 capable of generating friendly or neutral behaviors among rats serves as partner to the rats in the interaction. Meanwhile, we performed Principal Component Analysis to specify the mathematical model. The experimental results show that this mathematical model allows quantitative estimation of rat sociality. Likewise, the results reveal that rat sociality can be analyzed and modified in this robot-rat interaction system.

Neurologic examination takes an important role in diagnosis of the nerve system diseases. Neurologic medical staffs, especially the novices, need to be trained on this skill. There are many methodologies which can help to accumulate experiences, such as watching video, reading books, making use of the simulated patient (SP), and so on. However, the best way is to practice on the real patient. All the above methods have their own drawbacks such as lack of active interactions, limitation of multi-symptoms' reproducing, etc. To improve the training effectiveness, an arm robot is proposed in this paper for neurologic examination training as one part of the whole body patient robot named Waseda Kyotokagaku Patient (WKP). In this robot, various symptoms of the elbow force, biceps tendon reflex, involuntary action, and so on, are simulated and shown to the trainee. Finally, a set of experiments was carried out to verify our proposed mechanism and control system. Three neurologists with over 30 years' experience were invited to show their opinions on the reproductions of patients' symptoms, and to discuss the results. The effectiveness of this system was confirmed. The experimental results lead to the consideration that the approach is worth following in further research.

In the LTE-Advanced downlink, carrier aggregation (CA) employing multiple component carriers (CCs) is an essential technique to achieve a target peak data rate of 1 Gbps. 3GPP RAN WG1 meeting decided to adopt one transport block (TB) per CC, where the TB is the unit of channel coding and hybrid automatic repeat request (HARQ). When CA is applied to an LTE-Advanced UE, the soft buffer which is used for HARQ packet combining must be equally split according to the number of CCs, where the soft buffer size is one of the factors to in defining the LTE-Advanced UE categories. When soft buffer splitting is applied to UEs in a lower UE category, the soft buffer size per CC may not be sufficient and the performance of the HARQ packet combining is not ensured. In this paper, we propose a rate-matching scheme for CA and a new receiver suited to this rate matching scheme. Using the proposed scheme, degradation in the HARQ throughput performance due to the soft buffer splitting can be avoided and the same rate-matching scheme can be applied irrespective of the number of CCs. Simulations results show that the proposed scheme always provides better performance than that for equal splitting rate-matching scheme that reuses Rel-8 LTE rate-matching scheme.

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 recent years advanced robotic technology has seen more use in the medical field to assist in the development of efficient training systems. Such training systems must fulfill the following criteria: they must provide quantitative information, must simulate the real-world conditions of the task, and assure training effectiveness. We developed Waseda Kyotokagaku Airway series to fulfill all of those requirements. The WKA series we had developed does not consider external appearance such as patient skin, or internal appearance such as the pharynx, larynx, and esophagus. Moreover, the tongue mechanism of the previous system can not precisely measure the force applied by medical devices and cannot simulate muscle stiffness. In addition, the mandible mechanism of the previous system could not adequately reproduce various airway difficulties or apply force control. For these reasons, we propose the WKA-4, which has high-fidelity simulated human anatomy, and we have improved the mechanism over the previous system. We have also attached a lung to the proposed system to improve simulation of the real-world conditions of the task. In this paper, we present how to design several organs with various embedded sensors and actuators, for a conventional patient model with high-fidelity simulated human anatomy. We also present the control system for the WKA-4. Finally, we present a set of experiments carried out using doctors as subjects, and they gave their valuable opinions about our system.

Many patients suffer from swallowing disorders (dysphagia). There are many treatments for these disorders, such as swallowing therapy, surgery, and dietary modification. In our study, we focuse on dietary modification, a common approach. Normally, the swallowing is affected by food bolus properties such as hardness, stickiness and rheological characteristics, and dietary modifications can prevent swallowing disorder patients from suffering dysphagia (aspiration), as well as promote good nutrition. Based on these facts, our goal is to find foods which do not cause dysphagia, and develop food for swallowing disorder patients accordingly. Therefore, we are proposing an in-vitro Dynamic VFSS (Video Fluorographic Swallowing Study) simulation system which uses advanced robotics technology to mimic the dynamic process of swallowing and monitors the status and movement of the food bolus inside the system, for objective evaluation of the swallowing process. The dynamic VFSS simulation system consists of a head, mandible, neck, tongue, pharynx, and larynx which reproduce human anatomy. It is driven by 16 actuators with wire driving mechanisms. In this paper, we will present the dynamic VFSS simulation unit in detail. In addition, we will detail a set of the experiments carried out to determine whether food bolus properties can affect dysphagia or not. To observe the movement of the food bolus, we use a Video Fluoroscopy (VF) unit. The results of the experiments show that thickened boluses have a tendency to leave residue in the epiglottic vallecula. In contrast, liquids cause less residue, and increase the risk of dysphagia (aspiration). Moreover, this study shows that the frontal image, as well as the lateral image, is important for evaluating residual food in the oral- pharyngeal space.

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.

In Long-Term Evolution-Advanced (LTE-A), which is currently in the process of standardization in the 3rd generation partnership project (3GPP), carrier aggregation (CA) was introduced as a main feature for bandwidth extension while maintaining backward compatibility with LTE Release 8 (Rel. 8). In the CA mode of operation, since two or more component carriers (CCs), each of which is compatible with LTE Rel. 8, are aggregated, mobility management for CCs such as inter/intra-frequency handover, CC addition, and CC removal is needed to provide sufficient coverage and better overall signal quality. Therefore, the signaling overhead for Radio Resource Control (RRC) reconfiguration for the mobility management of CCs in LTE-A is expected to be larger than that in LTE Rel. 8. In addition, CA allows aggregation of cells with different types of coverage, and therefore, the signaling overhead might be dependent on the coverage of each CC assumed in a CA deployment scenario. This paper presents evaluation results on the CC control overhead with several CC management policies in some CA deployment scenarios, and shows that the increase in the control overhead is not significant even in a CA deployment scenario with overlaid picocells.

The number of patients with mental disorders is increasing in advanced countries. Many researchers are working to develop mental disorder model animals that contribute to development of new psychotropic drugs. However, we have some doubts about conventional mental disorder models. Therefore, the purpose of this study is to develop an experimental setup to create novel mental disorder model animals. We then developed a small mobile robot and a control system for the robot. Using them, we performed an experiment to develop a mental disorder model rat. In the experiment, we succeeded in developing a new depression model rat and also high activity model rat. These disorder models must be useful in the screening of new psychotropic drugs. In addition, the methodology we developed in this research will contribute to clarifying mechanisms of mental disorders.

Recently, in medical field, different training methods for medical staff have been proposed. However, the lack of knowledge on the real improvements of trainees makes difficult the real effectiveness of those proposed methods. Therefore, we are proposing an Active Training system for the effective medical training. The Active training system is characterized by providing quantitative information of the trainee's performance of the task to the trainee, simulating real-world conditions of the task, and assuring training effectiveness. In order to fulfill each of these characteristics, we have developed Waseda Kyotokagaku Airway No.3 (WKA-3) which makes it possible to obtain quantitative information for the trainee's performance and reproduce the various cases, individual differences for the airway difficulties for the simulating real-world conditions of the task. In this paper, we are proposing a patient scenario generation which can reproduce the characteristics of the patient simulating real-world conditions of the task for WKA-3. In emergent situation or surgical operation, the characteristics of patients are presented in the three parameters such as: patient initial conditions, time variant status change, and reflex action. By adjusting, and combining each of the three parameters, we can reproduce the various patient scenarios. In this paper, we also state how to generate the Patient Scenario Generation using the position control and virtual compliance control. Finally, a set of experiments has been carried out to the doctor subjects in order to verify effectiveness of the proposed Patient Scenario Generation, and discuss the doctors about the result of the experiments.

An active training system is characterized by providing quantitative information of the trainee's performance of the task to the trainee, simulating real-world conditions of the task, and assuring training effectiveness. For this purpose, the authors have been developing an Airway management training system. In particular, we have previously presented an evaluation model system to acquire quantitative information for the trainee's performance, and an actuated model system for real-world conditions of the task. In order to fulfill all of the characteristics of the active training system; in this paper, we would like to propose an integrated system, Waseda Kyotokagaku Airway No.3 (WKA-3) which integrates the function of both system models. For this reason, we have focused on embedding sensors and actuators with the link drive mechanism and the wire drive mechanism to a conventional patient model towards the development of a patient robot. In this paper, we present WKA-3 how to design the mechanism and how to redesign several organs to embed the sensors for the measurement of the trainee's performance. A set of experiment have been carried out to doctor subjects using the WKA-3 to verify the effectiveness of the proposed system by asking doctors to evaluate the proposed system.

In the domain of psychology and medical science, many experiments have been conducted referring to research on animal behaviors, to study the mechanism of mental disorders and to develop psychotropic drugs to treat them. Rodents such as rats are often chosen as experimental subjects in these experiments. However, according to some researchers, the experiments on social interactions using animals are poorly- reproducible. Therefore, we consider that the reproducibility of these experiments can be improved by using a robotic agent that interacts with an animal subject. We have developed a novel quadruped rat-inspired robot, the WR-2 (Waseda Rat No.2), based on the dimension and body structure of a mature rat. It is capable of reproducing the behaviors such as walking, mounting, rearing and grooming of the rat.

The emerging field of medical robotics aims to introduce intelligent tools to assist a physician. The main challenges for developing efficient medical robotic training systems are simulating real-world conditions of the task and assuring training effectiveness. High anatomic fidelity has been achieved in current systems. However, those training systems are designed to reproduce specific conditions of the task (passive training). In this research, we are focusing in developing an airway management training systems designed to reproduce various cases of difficult airway. Such difficulties (i.e. restricted mouth opening, various shapes of oral cavity including tongue swallowing, etc) may provoke traumas on different organs of the patient during an emergency situation. For this purpose, the authors have proposed the development of more advanced training tools. For this purpose, we have focused in embedding sensors and actuators to a conventional patient model towards the development of a patient robot (in previous research, authors have presented the evaluation model which embeds sensors). In this paper, we present an airway training system which embeds actuators into a mannequin. In particular, the mechanism design of the Waseda Kyotokagaku Airway No.2 (WKA-2) is detailed. The WKA-2 is composed of twelve active and one passive degrees of freedom; which are designed to reproduce the various cases of difficult airway. For this purpose, the WKA-2 reproduces the human muscles around the upper airway based on a wire driving mechanisms (a total of sixteen wires are used). In particular, the head of the model is composed of a tongue and mandible with translational and rotational movements around kinematic axis. In addition, we present the details of the kinematic model of WKA-2 which enable the robot to reproduce the airway difficulties. Finally, we presented the design of a tension sensor designed to measure the applied tension on each of the wire driving mechanism of WKA-2. As preliminary experiments, we reproduce several cases of difficult airways using WKA-2.

The emerging field of medical robotics is aiming in introducing intelligent tools to perform medical procedures. In particular, robotic researchers have been proposed advanced medical training systems to enhance motor dexterities of trainees. An efficient medical training system should be designed to simulate real-world conditions and to assure their effectiveness as the representation of the motor skills often differs among trainees. Up to now, several training simulators have been developed by medical companies designed to reproduce with high fidelity the human body. However, such devices are not designed to provide any information to trainees. Therefore, we have proposed the development of a patient robot which embeds sensors and actuators into a conventional human model. Due to its complexity, as a first approach; we are presenting the development of a suture training system designed to simulate the real-world task conditions as well as providing quantitative assessments. In particular; the Waseda-Kyotokagaku Suture No.2 Refined II is presented, which includes a new evaluation function to provide more detailed information of the task. A set of experiments were proposed to analyze the performance of trainees. From the experimental results, we could confirm its effectiveness to detect differences of the performance of trainees.

Up to now, there is no widely accepted quantitative evaluation scheme. Nowadays, an objective structured clinical examination has been proposed as a modern type of examination often used in medicine to test skills such as medical procedures, etc. The assessment of skills is realized by practical exams, in which students are evaluated by experienced examiner using a check list. However, the examiner lacks of information which cannot be obtained trough the simple observation of the task. Thanks to the advances in robot technology in embedded systems, etc.; more advanced evaluation tools can be conceived. For this reason, at Waseda University, we have proposed the development of a patient robot as an advanced evaluation tool to provide more detailed information of the task. As a first approach of our long-term research target, we have proposed the development of a suture/ligature training system which provides quantitative information of the movement of a dummy skin as well as information of the quality of task. In this paper; we describe the functionalities of the newest version, the Waseda-KyotoKagaku Skin No.2 Refined (WKS-2R), which has been designed to provide quantitative information of the task. In addition, we are proposing a new evaluation function which includes performance indexes and weighting coefficients. As a first approach, the weighting coefficients were determined by using the discriminant analysis. A set of experiments were proposed to confirm the effectiveness of the proposed evaluation function. From the preliminary results, the evaluation function was useful in detecting differences among different levels of expertise as well as detecting improvements during the training process by computing the learning curve.

Experiments on animals has been playing very important part in psychology, medical science, genetics and brain science. Rodents are one of the most popular experimental subjects in these experiments. In psychology and brain science, behavior test and analysis on rodents, especially rats, has been performed to clarify mechanisms of mind or brain functions. "Open-field test" is one of the most popular research methods to investigate their behavior. In the "open-field test," rats are released into the "open-field," circle or square, flat arena surrounded by walls, and their behavior parameters such as position, moving distance, number of grooming and rearing are measured. With conventional experimental setups, these parameters has been measured and recorded by humans. Observing and recording are heavy task for experimenters, and also involves some human errors and subjectivity. Therefore, we developed an autonomous experimental setup which measures rats' position, number of grooming and rearing in the open-field. In addition, an active tracking camera which takes high resolution images of the rat in the open-field was developed. To prevent losing tracks of the rat, a prediction model of rat's movement is developed and integrated into the control of this camera.

Airway management is provided by emergency medical technicians or anesthetists in order to save unconscious patients who are unable to breathe. Even though it is a basic technique, many accidents may occur when the procedure is not provided followed. In order to avoid any risks to patients, emergency medical technicians are required to practice airway management using training devices such as mannequins; which are designed to accurately reproduce the human anatomy. However, such training devices do not provide any quantitative information about the learning progress of trainees (passive training). For that purpose, we have proposed the development of a airway management training system which is designed to embed array of sensors so that quantitative information of trainees' performance can be acquired. In this paper, we are presenting the Waseda-KyotoKagaku airway No. 1 (WKA-1). The WKA-1 consists of three different kinds of array of sensors which are embedded into a conventional mannequin. In order to embed the array of sensors, we have simplified the design of some of the simulated organs (upper airway, oral cavity, tongue and teeth) of the mannequin. A set of evaluation parameters were proposed based on the information collected through the sensors. A set of experiments were proposed to experimentally verify the effectiveness of the proposed evaluation parameters to quantitatively detect differences among different levels of skills (anesthetists and unskilled persons).

we would like to clarify the basic factors necessary for a symbiosis between creatures and robots through the interaction experiments between rats and robots. In our previous studies, we developed a robot involving two levers and conditioned the rat to push these levers to obtain food by experimenter’s teaching. In this paper, we try to condition the rats to push the levers on the robot to obtain food by the robot autonomously showing its functions without experimenter’s teaching. On animal psychology, “shaping” is used to condition animals to perform difficult or complex behavior that would rarely occur spontaneously. By importing the concept of “shaping,” we developed an operational pattern generation algorithm for the robot that enabled it to autonomously operate to show the rats its function. We then conducted an interaction experiment for evaluating this algorithm and confirmed the effectiveness of it. Thus, we proposed to import the concept of “shaping” into robot’s behavior generation to enable it to autonomously show creatures its functions.

High-speed downlink packet access (HSDPA) is specified in the 3rd generation partnership project (3GPP) to cope with the increasing demand for high-speed Internet-based multimedia services. This paper presents field experimental results of the user throughput performance in HSDPA to clarify the effects of the maximum number of multi-codes, transmit diversity, and advanced user equipment (UE) such as receive diversity and a chip equalizer. The field experimental results show that 15-multi-code UE, transmit diversity, and receive diversity achieve the peak throughput of 6.5, 8.5, and 10.2 Mbps, respectively, at the average moving speed of 30 km/h in an actual multi-path fading propagation channel, and the average received signal-to-interference power ratio (SIR) is 24 dB. Furthermore, the results show that transmit diversity, receive diversity, and the chip equalizer can improve the average throughput to 27.0%, 54.6%, and 12.8%, respectively, compared to the conventional single antenna Rake receiver when the average received SIR is 16.3 dB.

In this paper we introduce a blind parameter identification algorithm for Orthogonal Frequency Division Multiplexing (OFDM) signals. The algorithm correlation-based processes automatically estimate all parameters of OFDM signals with a blind process that works from a limited amount of data without any prior information. We also derive novel identification performances of algorithms under various conditions, assuming actual conditions in feasible systems: data offset, AWGN, frequency offset, and fading channels. The algorithm is essential for two systems: first, Cognitive Radios, one of the most exciting being radios that change fundamental parameters frequently to provide high throughput and high quality of services; and, second, Radio Monitoring Systems that detect illegal signals transmitted by unlicensed devices.

We clarify the basic factors necessary for a symbiotic relationship between humans and robots. However, evaluating interaction between humans and robots is difficult due to a number of uncertain factors in human communication. Therefore, less sophisticated creatures, rats, were first selected, and we conducted interaction experiments between rats and robots. In our previous studies, we could not conduct these experiments for over 2 hours. We then developed a new experimental system to conduct the experiments without time restrictions. Using this system, we conducted two interaction experiments. In one experiment, the robot, meeting a rat's request, could live symbiotically with the rat. In the other experiment, the robot, behaving sequentially without having met the rat, could control the rat. This paper investigates the factors for a symbiotic relationship between a rat and a robot by comparing the two experiments.

We have developed an adaptive receiver improved by a function which automatically identifies the modulation mode from many kinds of modulation modes. Several tests were carried out for the evaluation by PC simulation, under laboratory environment, under outdoor environment. By the evaluation tests, identification probability of 90% or better was acquired at S/N = 6 dB for BPSK, S/N = 6 dB for QPSK, S/N = 6 dB for 8PSK, S/N = 6 dB for pi/4 shift QPSK and S/N = 4 dB for 16QAM. The identification probability of the proposed algorithm was almost same under both of static and dynamic environment, although the dynamic environment was influenced by fading and multipass phenomena, etc.

We implemented indoor and outdoor evaluation tests on the developed modulation mode identification algorithm using a experiment system with software radio techniques. In the indoor evaluation test, identification probability test was executed on S/N and fading conditions. As the result, it was confirmed that modulation mode identification probability of 90% or better was achievable at S/N /spl ges/ 1 dB for FSK, S/N /spl ges/ 13 dB for MSK, and S/N /spl ges/ 9 dB for GMSK (BbT=0.3 dB). Additionally, it was confirmed from identification test results on GMSK that identification probability deteriorates as BbT product decreases. Furthermore, it was confirmed that modulation mode can be identified under the fading environment with Rayleigh fading 50 Hz. In the outdoor evaluation test, the test source was mounted on a vehicle and identification probability test was executed. Its result showed that identification probability of 94% or better was possible with the proposed algorithm under the dynamic environment where it was influenced of fading and multipath.

A modulation parameter measurement algorithm used as support algorithm of automatic modulation identification algorithms in a radiowave monitoring system is described. Precise and fast measurement methods which measure modulation parameters, such as modulation index and the baseband filter's B/sub b/T product, are proposed. Because of the trade off of precision and process speed of modulation parameter measurement, the results of the most suitable sampling rate on the basis of experimental verifications are described.

We developed an identification algorithm that can distinguish twelve kinds of modulation modes using a blind process aimed at automatic identification of unknown modulated signals. We also developed an adaptive receiver, installed this algorithm, and we carried out an experiment to evaluate the receiver's ability. By the result of the validation experiment, for linear digital modulation modes with S/N /spl ges/ 3 dB, for GMSK of nonlinear digital modulation modes with S/N /spl ges/ 18 dB, and for the FM of analog modulation modes with S/N /spl ges/ 12 dB, we got a performance of identification probability of over 90 % respectively. Furthermore, based on the identification results, we evaluated the adaptive demodulation process by using the developed system and confirmed its effectiveness.