There are patients that cannot produce bioelectric signals such as patients with advanced stages of Amyotrophic Lateral Sclerosis or that have suffered severe spinal cord injury, are unable to use assistive devices such as the exoskeleton HAL. This paper proposes a non-invasive brain activity scanning method for collecting the patient’s movement intentions by developing a hybrid sensor that can measure both optical and bioelectrical signal of a same spot simultaneously and to evaluate it. The developed sensor consists of holography lasers and electrodes. Holography laser contains emitter and receiver inside it. In order to evaluate the hybrid sensor two kinds of experiments were carried out: 1) Data Collection Experiment in which the optical density was found to be high when the participant was in relaxation state. On the other hand, while the participant was executing mental tasks such as algebraic calculations the optical density lowered. 2) Proof of concept Experiment in which the participant tried to move the upper limb assistive device 10 times. The upper limb movement was recorded 24 times during this period. However out of this 24 times, the upper limb movement corresponded to the participant’s intention 7 times that was recorder 5sec before or after subject started calculation. We developed a hybrid sensor that can collect both kinds of optical and bioelectrical signal from the same spot on the scalp was developed and evaluated in order to measure brain activity by using optical and bioelectrical data.

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Walking gait based on actual machine elements that capture the major features of human locomotion may enhance the understanding of human leg morphology and control, and provide necessary background science for the design and control of human-robot exoskeleton interaction system. This paper describes an investigation into the biomechanical effects of human lower limb joints during different loaded walking. Healthy volunteers walked on a level with different loaded (0kg, 10kg, 20kg, 30kg). The experiment results of human walking motion may give the base which joint of power-assisted lower extremity robot should be actuated, and what driving method should be used. At the same time, the kinematics and kinetics data of human walking motion give some bases for the choose of the actuator.

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The objective of this study is to design a robot system to assist the rehabilitation of patients so that they can afterwards do various daily activities. It is difficult to determine the desirable posture of a 9-DOFs exoskeleton manipulator in such a system and each joint control design as well. In this paper, we resolve the difficulties by mapping the kinematics of a human arm to that of the manipulator so that we can avoid going through the ill-postured configurations while searching for the desired solutions, and then reach the desired rehabilitation motion as precisely as possible. In addition, this study combines electromyography (EMG) and force sensor to detect the patient’s motion on his/her volition, so that the rehab-robot can support the human’s upper limb appropriately to fulfill the intended motion. For validation of our rehab-robot design, experiments are conducted and promising results are obtained.

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Our goal is to try to enhance the QoL of persons with hemiplegia by the mean of an active motion support system based on the HAL’s technology. The HAL (Hybrid Assistive Limb) in its standard version is an exoskeleton-based robot suit to support and enhance the human motor functions. The purpose of the research presented in this paper is the development of a new version of the HAL to be used as an assistive device providing walking motion support to persons with hemiplegia. It includes the realization of the single leg version of the HAL and the redesign of the original HAL’s Autonomous Controller to execute human-like walking motions in an autonomous way. Clinical trials were conducted in order to assess the effectiveness of the developed system. The first stage of the trials described in this paper involved the participation of one hemiplegic patient who has difficulties to flex his right knee. As a result, the knee flexion support for walking provided by the HAL appeared to improve the subject’s walking (longer stride and faster steps). The first evaluation of the system with one subject showed promising results for the future developments.

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>We proposed a framework of using neural oscillators to control a robotic suit which learns to synchronize with the human user’s motion. The robotic suit is a lower limb exoskeleton consisting of four actuators which are fixed to the places where the human hip joints and knee joints are. Each actuator has a built-in harmonic drive gear which is equipped with a torque sensor fixed on the flex-spline. The torque sensor helps to measure the mutual joint torque, which will be generated by once there is any differences between human’s and suit’s movement. The neural oscillator connected to each joint controls each actuator through synchronizing the actuator’s desired joint angle with the feedback mutual joint torque. Proportional-integral-derivative (PID) control is then used to determine the real joint angle of each actuator. We have conducted experiments to show whether: 1) the synchronous movement of robotic suit is realized; 2) the synchronized movement has the application potential for walking assistance and rehabilitation. The results showed the potential of applying the synchronization based control to the robotic suit for walking assistance and rehabilitation purposes.

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