This paper introduces a crawler robot equipped with a movable bending point mechanism that allows it to bend anywhere along its trunk. The robot features a movable motor unit that travels along its body, dynamically adjusting the bending initiation point. This enables the robot to move forward and backward, bend its body, and shift the bending position as needed. By integrating these capabilities, the robot enhances its ability to navigate obstacles and confined spaces. We develop three statics-based models to predict the robot’s performance in escaping narrow spaces, climbing steps, and crossing ditches. These models demonstrate that adjusting the bending point improves traversal capabilities, a finding corroborated by experiments with the physical robot.

Movement/walking assistance devices have the great advantage of supporting quality of life for the elderly in an aging society. To strike a balance between efficiency of movement and employment of the elderly user's own body, we developed a smart mobility system called Tread-walk, which is controlled by the user walking on a treadmill and amplifies the user's walking speed. Since the user's walking speed is different from the speed at which the Tread-walk moves, users experience a mismatch between their visual optical flow and somatic sense. In this article, we validate the feasibility of an amplifying gain decision method that analyzes user brain activity. To control Tread-walk, the visual sense is integrated with somatosensation in the parietal area of the brain and controlled in the medial prefrontal cortex. Therefore, first, we measure the parietal area when the participants walk while looking at their virtual optical flow. Second, we measure the medical prefrontal cortex when the participants control Tread-walk 2. These experiments are carried out for a variety of speed amplifying gains. We find that the brain activates significantly at amplification gain K = 1.1-1.7 in the virtual optical flow experiment and K = 1.5-2.0 in the Tread-walk experiment; this brain activation represents the amplification gain at which the visual and somatosensory senses seem to receive similar input. In conclusion, the brain would activate the most significantly at the most appropriate amplification gain.

In situations such as endoscopic surgeries, a leader cannot use their hands to instruct the other surgeons to perform a task on the monitor because he/she must use both hands to control the surgical equipment. Although there are several pointing methods such as eye gaze tracking, these methods are not suitable for endoscopic surgeries, where optical sensors (e.g. infrared sensors) cannot be used due to the existence of physical obstacles in the operating theater. Therefore, an assisting pointing device apparatus that directly measures the behavior of users and is not based on hands is specifically needed. To tackle this problem, we built a pointing device that measures the tilt angle of a user's head by gyro and acceleration sensors. Furthermore, we evaluated the performance of our device compared to that of a mouse using statistical analysis based on Fitts' law and other commonly used parameters. We considered a mouse as a benchmark to clarify the limitations and possible usage of our device. We found that, although it does not perform as good as a mouse, our device can still suitably perform as an assisting device for limited usage such as for tracking pre-defined lines.

Continuous, easy-to-implement, accurate inference of intended joint angles is important for effectively controlling powered prosthetic devices that can improve the lives and capabilities of upper-limb amputees. Estimation of intended joint angles is difficult because conventional biosignals are not directly related to the intended angle motion. In previous work, we began to address this issue by confirming that both transra-dial amputees and intact subjects, the measured deformation of the muscle bulge on the skin surface change according to the intended wrist joint angle. This paper presents a continuous prosthesis wrist joint control method using this deformation signal. We here verify the effectiveness of the distribution of the muscle bulge for accurate and stable wrist joint angle control in real time. The wrist joint angles were calculated in real time from a muscle viscoelastic model using the previously determined algorithm. We compared the error between measured and estimated angles with a conventional method, the Voigt model, and the KelvinVoigt model. Experimental results obtained for three intact people over three trials of wrist movement tasks gave the accuracy and stability of 7.96±6.16°when using the Voigt model; this is a similar performance compared to related work using a surface electromyogram. A method for continuously controlling the wrist joint angle for a prosthesis using the distribution of the muscle bulge was thus successfully established.

The increase in care-receiver/caregiver ratio is becoming a social problem in Japan, one factor in which is the increase in the number of falls in the elderly. The purpose of this study is to develop a balance training ability system for fall prevention. To effectively improve balance ability while walking, dynamic training specialized for somatic sensation is useful. We developed a system that greatly improves balance ability by removing visual information of the outside world during gait training and by producing visual feedback of somatic sensation information, consisting of joint angle information about the whole body and foot pressure distribution information, that is, somatic sensation information used for gait. One technical problem with this system is the selection of display method at the time of visual feedback. Therefore, in this paper, we hypothesize that the training effect improves when a combination of foot pressure information and joint information is used. As specific presentation information, center of pressure (hereinafter called CoP) and ideal CoP traces derived from each joint angle were used. The ideal CoP trace is shown with a broken line connecting the heel, metatarsal and toe-tip part of the foot, and is updated every 10 walking cycles by changing the transverse coordinates of the metatarsal and toe-tip. To verify the abovementioned hypothesis, we created a machine equipped with the feedback system, and verified and tested it. To create the feedback system, the relationship between each joint angle in the body and ideal CoP traces were derived by a multiple regression analysis of the gait data (foot pressure distribution, joint angle) of young, physically unimpaired volunteers. In the verification experiment, we compared the training using the feedback system to that without in a visual sense cutoff state. The standard deviation a of right-and-left directions of the CoP traces was used as a performance index of balance ability. Increased a indicates reduced dynamic balance ability. We found that a increased by 0.61 times by feedback training, which was a significant decrease, and by 0.84 times after the visual sense interception training. A significant difference (p < 0.05) was seen between the effects of these two training types, suggesting that dynamic balance ability is improved by our feedback system. In future, we will verify the long-term training effects over several months or years, as well as the improvement in motivation over training.

An essential tremor (ET) is a disorder that causes involuntary oscillations. ET patients face serious difficulties in performing such daily living activities as eating, drinking, and writing. We have been developing an exoskeleton to suppress tremors and support the eating movements of ET patients. The objective of this study is to propose a passive mechanism that prevents the appearance of the compensatory shoulder movement without using an actuator. The basic concept of this study is developing the mechanism to coordinate two DoF movement of elbow joint. Two DoF movement of elbow joint is constrained to passive one DoF by our wearable robot. The mechanism of our robot and constrain mechanism is optimally designed to reduce the compensatory movement during eating movement. To develop such mechanism, we first analysed the eating movement to derive the required specification of the mechanism. Then, we proposed a prototype based on the requirement. Finally, we evaluate the effect of the prototype to reduce the compensatory movement. It is confirmed that the proposed prototype had great effect on the reduction. As a future work, we will optimize the structure and the material of the mechanism to reduce the weight of the mechanism.

Mechanical performance of a surgical robot can be evaluated and improved based on a working score; however, intuitive operability cannot be evaluated in this way. We propose a method that measures the user's brain activity for evaluating intuitive operability from the perspective of cognitive science. We hypothesized that hand-eye coordination, such as the slave configuration for the endoscope, has the greatest effect on intuitive operability, because it is the cause of physical differences between a human and a robot. The objective of this paper is to clarify the appropriate slave configuration for the endoscope to study hand-eye coordination using brain activity measurements. In the experiment, we used a brain imaging device, optical topography, to measure the users' brain activity while they controlled the hand-controller to position the tip of the virtual arm on the target. The experiment was carried out a number of times with the virtual arm position configured in a variety of ways. According to the results, some subjects showed peak performance with a specific slave configuration. We conclude that the slave configuration with the highest brain activity depends on the body image, which is a spatial symbol in the human brain from the perspective of cognitive science.

Robotic gait training has been introduced recently in rehabilitation, and the related researches have been conducted to propose more effective mechanism and control. To automate gait training, position control with reference trajectory has been adopted in many researches. However, there remain problems such as enhancing self-dominated gait or adapting to asymmetry or individual difference to apply robotic gait training to moderately affected hemiplegia patient. To solve this problem, we quantified the manual pelvic assistance (handling) provided by physical therapy, which can enhance patient's self dominated gait individually. In this paper, the physical model of handling was proposed based on the measurement and verified by multiple regression analysis.

Recently, a large amount of stroke survivors are suffering from motor impairment. However, existed therapy interventions have limited effects to restore normal motor function. Thus, we proposed a novel control strategy for gait rehabilitation of hemiplegic patients. The whole system consists of a Functional Electrical Stimulation (FES) device and Treadmill-Walk system. FES contributes to improve the quality of the gait based on real-time adjustment of gait pattern. During gait, the electrical stimuli from separate output channels of an FES device are launched to stimulate two lower extremity muscles (Tibialis Anterior (TA) and Hamstrings). Stimulus launching procedure is based on identifying subject's gait state (stance and swing phases). According to the current variation of treadmill motor, gait phase and muscle activation of lower limbs can be determined during walking on Treadmill-Walk. Three able-bodied subjects simulated hemiplegic patients in the experiment. The results indicated that the proposed method is a safe, feasible and promising intervention.

We have been developing the new personal mobility aid, "Tread-Walk 1," which is controlled by the driver's walking pace and amplifies walking velocity. The Tread-Walk 1 not only assists mobility but also helps the elderly maintain their physical abilities. However, the turning movement of the Tread-Walk is likely to be unstable, because the Tread-Walk is controlled by walking. In this paper, we focus on the stable turning movement of the Tread-Walk 1. First, we simulate the centrifugal force applied to the driver, which was not considered in our previous report. Then, a new algorithm to realize stable turning movement is established by measuring the driver's standing position. Finally, the developed algorithm for the turning movement of the Tread-Walk 1 is evaluated by measuring the handle grasping time. With the new algorithm, the Tread-Walk 1 turned steadily and driver did not lose their balance.

To develop a gait rehabilitation robot for hemiplegic patients, quantitative evaluations of patient ability is needed. Patient's walk phase, which includes time balance of stance and swing legs, is one of the most useful indexes. However, conventional methods measuring walk phase require laborious preparations. In this paper, a novel algorithm estimating walk phase on a treadmill by observing DC motor current is proposed. In comparison of this algorithm and conventional methods, it was verified that the proposed algorithm had as the same accuracy as foot switch. Moreover, the proposed algorithm could estimate stance phase in 0.2 (s) errors between measurements of force plate mostly (4 out of 5 healthy subjects). However, result from the 5th subject showed that the proposed algorithm had erroneously identified stance phase as swing phase when little body weight loaded on leg. This characteristic is often observed in hemiplegic gait. Therefore, the proposed algorithm might need improvement of motor current threshold. However, this algorithm had capable of estimating the time of loading body weight on leg, and thus could be useful as a quantitative evaluation tool.