This paper presents MoonWalker, a lower limb exoskeleton able to sustain part of a user’s bodyweight. This orthosis can be used for rehabilitation, to help people having weak legs, or to help those suffering from a broken leg, to walk. It can also be used as an assistive device helping people carrying heavy loads. Its main characteristic is that a passive force balancer provides the force to sustain bodyweight. An actuator is also required, but is used only to shift that force the same side as the leg in stance. Consequently, MoonWalker requires very low energy to work on flat terrains. That motor can provide also a part of the energy to climb stairs or slopes. We believe that this approach can help improving energetic autonomy of lower limb exoskeletons.

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The design of a robotic exoskeleton often focuses on replicating the kinematics of the human limb that it is connected to. However, human joint kinematics is so complex that in practice, the kinematics of artificial exoskeletons fails to reproduce it exactly. This discrepancy results in hyperstaticity. Namely, uncontrolled interaction forces appear. In this paper, we investigate the problem of connecting an exoskeleton to a human member while avoiding hyperstaticity; to do so, we propose to add passive mechanisms at each connection point. We thus introduce a formal methodology for avoiding hyperstaticity when connecting wearable robotic structures to the human body. First, analyzing the twist spaces generated by these fixation passive mechanisms, we provide necessary and sufficient conditions for a given global isostaticity condition to be respected. Then, we derive conditions on the number of Degrees of Freedom (DoFs) to be freed at the different fixations, under full kinematic rank assumption. We finally apply the general methodology to the particular case of a 4 DoF shoulder-elbow exoskeleton. Experimental results allow to show an improvement in transparency brought by the passive mechanism fixations.

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Despite the great diversity of teleoperator designs and applications, their underlying control systems have many similarities. These similarities can be exploited to enable inter-operability between heterogeneous systems. We have developed a network data specification, the Interoperable Telerobotics Protocol, that can be used for Internet based control of a wide range of teleoperators. In this work we test interoperable telerobotics on the global Internet, focusing on the telesurgery application domain. Fourteen globally dispersed telerobotic master and slave systems were connected in thirty trials in one twenty four hour period. Users performed common manipulation tasks to demonstrate effective master-slave operation. With twenty eight (93%) successful, unique connections the results show a high potential for standardizing telerobotic operation. Furthermore, new paradigms for telesurgical operation and training are presented, including a networked surgery trainer and upper-limb exoskeletoncontrol of micro-manipulators.

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Pathological tremor constitutes the most common movement disorder, and is increasing its prevalence with ageing. Treatment forms range from drugs to surgery in those patients refractory to drugs, however, tremor is not effectively managed in about 25% of patients. According to this, new management techniques such as wearable robots that take advantage of selective biomechanical loading seem an interesting alternative. Our objective is to design robotic exoskeletons which suppress tremor, letting the user perform a voluntary movement, by means of intelligent control approaches that include accurate tremor models. In this context, we propose a two-stage algorithm for real-time estimation of time varying tremor amplitude and frequency. It is based on the assumption that tremor alters voluntary motion in an additive manner, and happens in a higher frequency band. The two-stage algorithm first generates an estimation of voluntary movement based on its inherent slower dynamics, and then removes it from the total motion, directly providing an estimate of tremor. This tremor estimation is then fed into an adaptive filter, which provides instantaneous tremor characteristics. Accurate and robust tremor amplitude and frequency estimates are obtained.

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A number of rehabilitation robots were developed and used to promote the recovery of motor functions in the upper extremities of stroke patients. Current clinical evidence suggests that the robotic rehabilitation is much more effective in acute than in chronic patients. One important difference between the two groups is the amount of the baseline skills with which they start the training. The goal of our research was to get a further insight into this issue by conducting an experiment in healthy subjects. As a model of motor learning, simulating the process of robotic rehabilita-tion, we developed a methodology for the transfer of a motor skill from an expert to a novice subject by using a haptic interface integrated with the virtual environment. A motor skill was implemented in the form of a challenging computer game, and the haptic interface provided the assistive forces during playing. To assess if and how a level of prior skills affects the motor learning assisted by the robot, the game was played by both novice and partially trained players. The results showed that the assistance was effective only in the novice players, while the trained players experienced the assistive forces as a disturbance. In the context of neurorehabilitation, this finding implies that the existing experience of chronic patients, i.e., the established motor patterns (e.g., compensatory strategies), has to be considered when designing the assistance that would actually promote (instead of disturbing) the learning process.

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