Backdrivability is a keyword with rising importance, not only in humanoid robots, but also to wearable robots. Power assist robots, namely exoskeletons are expected to provide mobility and independence to elderly and people with disability. In such robots, without backdrivability, error between human and robot motion can be painful; sometimes dangerous. In this research, we apply a type of hydraulic actuator, specially designed to realize backdrivability, to exoskeletal robot to improve backdrivability. We present the basic methodology to apply such hydraulic actuator to wearable robots. We developed prototype of knee joint power assistexoskeleton and performed fundamental tests to verify the design method validity.

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Many researchers are studying and developing various kinds of man-machine systems. Especially, a wearable robot, such as anexoskeleton power suit, is one of the most remarkable fields. In this field, more accurate and reliable sensing system for detecting human motion intention is strongly required. In most of conventional man-machine systems, torque sensors, tactile pressure sensors and EMG sensors are utilized in a man-machine interface to detect human motion intention. These sensors, however, have some limitations. For example, it is hard to install and secure torque sensors on the joints of a human body. It is not easy to correlate the data from a tactile pressure sensor to the human motion intention. Although the EMG sensor can detect human motion intention, the sensor system is complex and expensive, and suffers from electric noise. We have been developing an innovative sensor suit which, just like a wet suit, can be conveniently put on by an operator to detect his or her motion intention by non-invasively monitoring his or her muscle conditions such as the shape, the stiffness and the density. This sensor suit is made of soft and elastic fabrics embedded with arrays of MEMS sensors such as strain gauges, ultrasonic sensors and optical fiber sensors, to measure different kinds of human muscle conditions. In the previous paper, the muscle stiffness sensor for detecting muscular force was developed according to the fact that the muscle gains its stiffness as it is activated. Its superior performance was reported through experiments in which the sensor was applied for the assisting device for the disable. In this paper, the ultrasonic sensor disk is proposed as one of the sensor disks embedding the sensor suit. This sensor is based on an original principle and non-invasively detects activity of specific muscle. It is clear that the square of ultrasonic transmission speed is in proportion to the elasticity of the object and in inverse proportion to the density. It is estimated that the elasticity and density of the muscle increase or decrease as the muscle is energized. Then, it is hereby expected that the muscular activity is measured by the ultrasonic sensor. In this study, the feasibility of an ultrasonic sensor for detecting muscular force is shown thr- ough experiments.

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The following topics are dealt with: medical robotics; nanobiotechnology; regenerative medicine; human-machine interaction; exoskeleton; rehabilitation medicine; prosthesis; biomimetics; surgery; and patient diagnosis.

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Robotic gait rehabilitation is at least as effective as conventional gait training in stroke survivors. Patients must be assisted as needed in order to improve affected gait patterns. The combination of impedance control and series elastic actuation is a viable actuation principle to be used for human robot interaction. Here, a new promising electric series elastic actuated joint is developed. The large torque bandwidth limit at 100 Nm is 6.9 Hz. With a total weight of 3.175 kg it is possible to directly mount the actuator on the exoskeleton frame. The actuator is capable of providing sufficient torque at normal walking speed. Full patient assistance during gait and free motions without impeding the gait pattern are possible. The actuator allows isometric measurements up to 100 Nm and the patient’s progress in robotic rehabilitation can be evaluated.

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Task based repetitive therapy has been proposed to help stroke survivors to regain functional control of arm movement. We developed a wearable exoskeleton rehabilitation robot with associated control algorithm and safety protection mechanisms, and a graphic user interface that is easy to use and intuitive to patients and therapists, as the framework for automated and customizable robot-assisted rehabilitation system for clinic and home based therapy. The system was tested in two feasibility studies. The first study involved 6 patients to receive therapeutic training during three time weekly clinic visits for 4 weeks. The second study set up the robot-assisted rehabilitation system at patient’s house, where the therapeutic training was practiced on a daily base. Two patients were recruited for the home application study. Patients’ performances were assessed using clinical evaluation tools, including Wolf Motor Function Test and Fugl Meyer Assessment (FMA), both before and after the training. The performances of patients during the training weeks were also objectively evaluated by using the robot sensory data.

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