Gait training of stroke survivors is crucial to facilitate neuromuscular plasticity needed for improvements in functional walking ability. Robot assisted gait training (RAGT) was developed for stroke survivors using active leg exoskeleton (ALEX) and a force-field controller, which uses assist-as-needed paradigm for rehabilitation. In this paradigm undesirable gait motion is resisted and assistance is provided towards desired motion. The force-field controller achieves this paradigm by effectively applying forces at the ankle of the subject through actuators on the hip and knee joints. Two stroke survivors participated in a 15-session gait training study each with ALEX. The results show that by the end of the training the gait pattern of the patients improved and became closer to a healthy subject’s gait pattern. Improvement is seen as an increase in the size of the patients’ gait pattern, increased knee and ankle joint excursions and increase in their walking speeds on the treadmill.

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Common actuators have important drawbacks for use in an exoskeleton type of rehabilitation (training) robot. Either the actuators are heavy, complex or poor torque sources. A new actuation system is proposed and tested that combines a lightweight joint and a simple structure with adequate torque source quality. It consists of a servomotor, a flexible Bowden cable transmission, and a force feedback loop based on a series elastic element. Measurements show that performance is sufficient for use in a gait rehabilitation robot.

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Robotics is emerging as a promising tool for training of human functional movement. The current research in this area is focused primarily on upper extremity movements. This paper describes novel designs of three lower extremity exoskeletons, intended for gait assistance and training of motor-impaired patients. The design of each of these exoskeletons is novel and different. Force and position sensors on the exoskeleton provide feedback to the user during training. The exoskeletons have undergone limited tests on healthy and stroke survivors to assess their potential for treadmill walking. GBO is a gravity balancing un-motorized orthosis which can alter the gravity acting at the hip and knee joints during swing. ALEX is an actively driven leg exoskeletonwhich can modulate the foot trajectory using motors at the joints. SUE is a bilateral swing-assist un-motorized exoskeleton to propel the leg during gait.

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Technology assisted therapy has the potential to transform rehabilitation options available, and to dramatically increase the reach of today’s healthcare system. Yet challenges persist in rendering translational application designs that optimize the full potential of technology and create value for the patient and the therapist. In a step towards optimizing value of technologies for practical applications to support very weak patients who might otherwise be unable to participate in traditional therapies, an integrated sensory motor training station was designed and developed. Inspired by recent neuroscientific research findings the goal of the design was to provide concurrent first person perspective immersive action observation of both virtual and real elements for motor and sensory experience; the system incorporates a virtual limb proxy that can be personalized and actuated by the robot and that is accompanied by exercise practice in peripersonal space for a plasticity promoting experience for the hand and arm. The station uses virtual reality and real objects for visual sensory experience, real objects also provide tactile sensory experience, and an exoskeleton upper limb robot provides assistance to patients. For many patients, successful movement and movement intensity required in rehabilitation is not achievable without the robot assistance. The multi-sensory features of the system promote a top-down strategy for training the upper limb (hand and arm) complementing the robot training; the system is ideally targeted for weak patients and those with tactile or proprioception sensory loss and those who are known to benefit from multi-sensory experiences.

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Biotechnology is a science that is growing rapidly. The objective of this project is to advance in the field. Specifically it aims to study applications of kinematics in the field of human-machine interfaces namely exoskeleton and prosthesis designs for the human hand. The methodology used in this project consists of three phases. First a theoretical model of the hand kinematics is defined from medical literature. This is done by synthesizing the hand into its simplified parameters to define a robotic model. The adjustment of the theoretical model to a hand is then done by capturing the movement using computer vision. This is done by using markers on each nail to be able to estimate their poses which consist of their spatial orientation and position. This sequence permits estimating the movement of the entire hand. Dimensional kinematic synthesis is finally applied to adapt the theoretical model to the dataset provided by computer vision. This is done by defining the equations of the movement of the theoretical hand model and is then solved by a numerical solver. This allows the creation of a persona-lized hand model that can then be used for the study of correspondences between electromyography (EMG) and the movements of the hand. In conclusion, this project has designed a robust algorithm for the tracking and estimation of the poses of the nails of the hand. It has also defined the movement equations and created an application to solve them. This has led to the nding of many nonanthropomorphic models that can be of use in the design of exoskeletons.

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