A haptic apparatus may include a plate element positionable to extend over an anatomical segment of a user, and an elongate member coupled to the plate element and configured to be movably mounted onto the anatomical segment so as to remain substantially vertical and substantially perpendicular to the anatomical segment while the anatomical segment undergoes a motion. The haptic apparatus may further include a motion restrictor responsive to a control signal to impede the motion of the anatomical segment by generating an opposing force along the elongate member in a direction normal to the anatomical segment, thereby providing tactile feedback to the user.

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An innovative sensor suit is developed, which 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 muscle stiffness sensor, ultrasonic sensors, accelerometers and optical fiber sensors, to measure different types of human muscle conditions. Compared with conventional sensors used in man machine interfaces, the proposed sensor suit is soft, flexible, lightweight, easy to wear, accurate and reliable. More importantly, the sensor suit is auto-adaptive to an individual operator and does not impede motion against the operator. Furthermore, a failsafe mechanism using special hardware and active sensing software is incorporated in the sensor suit to ensure the safety and reliability. As a result, the sensor suit is ideal for use in man-machine systems, particularly the DARPA exoskeleton power suits. In this case, the sensor suit will be worn by the operator under the exoskeleton power suits. The sensor suit, with its distributed sensing capability, will provide accurate and reliable information about the operator’s motion intention which is needed for controlling the power suit to accurately follow the operator s motion intention.

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Metabolic studies have shown that there is a metabolic cost associated with carrying a load (Griffin et al, 2003). Further studies have shown that by applying forward propulsive forces a person can walk with a reduced metabolic rate (Farley & McMahon, 1992 and Gottschall & Kram, 2003). Previous work on exoskeleton design has not considered the passive dynamics of walking and has focused on fully actuated systems that are inefficient and heavy. In this thesis, an under-actuated exoskeleton is presented that runs parallel to the human leg. The exoskeleton component design is based on the kinematics and kinetics of human walking. The joint components of the exoskeleton in the sagittal plane consist of a force-controllable actuator at the hip, a variable-damper mechanism at the knee and a passive spring at the ankle. A state-machine control strategy is written based on joint angle and ground-exoskeleton force sensing. Positive, non-conservative power is added at the hip during the walking cycle to help propel the mass of the human and payload forward. At the knee, the damper mechanism is turned on at heel strike as the exoskeleton leg is loaded and turned off during terminal stance to allow knee flexion.

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BWSTT has become an accepted standard of care in gait rehabilitation methods. This type of locomotor training has many functional benefits, but the physical labor costs are considerable. To reduce therapist effort and improve the repeatability of locomotor training, three groups have developed commercially available robotic devices for assisted stepping. The purpose of these robotic devices is to augment locomotor rehabilitation by decreasing therapist manual assistance, increasing the amount of stepping practice, while decreasing therapist effort. Current clinical studies have yielded positive and promising results in locomotor rehabilitation inpatients with neurologic impairments of stroke or SCI. The potential benefits from robotic technology are significant for clinical use and research. As further research is conducted, rehabilitation therapists and patient outcomes will be able to contribute to the development of current and future technologies.

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The exoskeleton robot, serving as an assistive device worn by the human (orthotic), functions as a human-amplifier. Setting the human machine interface (HMI) at the neuro-muscular level may lead to seamless integration and an intuitive control of theexoskeleton arm as a natural extension of the human body. At the core of the exoskeleton HMI there is a myoprocessor. It is a model of the human muscle, running in real-time and in parallel to the physiological muscle, that predicts joint torque as a function of the joint kinematics and neural activation levels. The study is focused on developing a myoprocessor based on the Hill phenomenological muscle model. Genetic algorithms were used to optimize model internal parameters using an experimental database that provides inputs to the model and allows for performance assessment. The results indicate high correlation between joint moment predictions of the model and the measured data. Consequently, the myoprocessor seems an adequate model, sufficiently robust for further integration into the exoskeleton control system.

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