Our goal is to enhance the quality of life of patients with hemiplegia by means of an active motion support system that assists the impaired motion such as to make it as close as possible to the motion of an able bodied person. We have developed the Robot Suit HAL (Hybrid Assistive Limb) to actively support and enhance the human motor functions. The purpose of the research presented in this paper is to propose the required control method to support voluntarily motion using a trigger based on patient’s bioelectrical signal. Clinical trials were conducted in order to investigate the effectiveness of the proposed control method. The first stage of the trials, described in this paper, involved the participation of one hemiplegic patient who is not able to bend his right knee. As a result, the motion support provided by the HAL moved the paralyzed knee joint according to his intention and improved the range of the subject’s knee flexion. The first evaluation of the control method with one subject showed promising results for future trials to explore the effectiveness for a wide range of types of hemiplegia.

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This paper presents a new gravity compensation method for an upper extremity exoskeleton mounted on a wheel chair. This new device is dedicated to regular and efficient rehabilitation training for post-stroke and injured people without the continuous presence of a therapist. The exoskeleton is a wearable robotic device attached to the human arm. The user provides information signals to the controller by means of the force sensors around the wrist and the arm, and the robot controller generates the appropriate control signals for different training strategies and paradigms. This upper extremity exoskeleton covers four basic degrees of freedom of the shoulder and the elbow joints with three additional adaptability degrees of freedom in order to match the arm anatomy of different users. For comfortable and efficient rehabilitation, a new heuristic method have been studied and applied on our prototype in order to calculate the gravity compensation model without the need to identify the mass parameters. It is based on the geometric model of the robot and accurate torque measurements of the prototype’s actuators in a set of specifically chosen joint positions. The weight effect has been successfully compensated so that the user can move his arm freely while wearing the exoskeleton without feeling its mass.

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