SUMMARYRobotic devices are well-suited to provide high intensity upper limb therapy in order to induce plasticity and facilitate recovery from brain and spinal cord injury. In order to realise gains in functional independence, devices that target the distal joints of the arm are necessary. Further, the robotic device must exhibit key dynamic properties that enable both high dynamic transparency for assessment, and implementation of novel interaction control modes that significantly engage the participant. In this paper, we present the kinematic design, dynamical characterization, and clinical validation of the RiceWrist-S, a serial robotic mechanism that facilitates rehabilitation of the forearm in pronation-supination, and of the wrist in flexion-extension and radial-ulnar deviation. The RiceWrist-Grip, a grip force sensing handle, is shown to provide grip force measurements that correlate well with those acquired from a hand dynamometer. Clinical validation via a single case study of incomplete spinal cord injury rehabilitation for an individual with injury at the C3-5 level showed moderate gains in clinical outcome measures. Robotic measures of movement smoothness also captured gains, supporting our hypothesis that intensive upper limb rehabilitation with the RiceWrist-S would show beneficial outcomes.

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The introduction of intrinsic compliance in the actuation system of assistive robots improves safety and dynamical adaptability. Furthermore, in the case of wearable robots for gait assistance, the exploitation of conservative compliant elements as energy buffers can mimic the intrinsic dynamical properties of legs during locomotion. However, com-mercially available compliant components do not generally allow to meet the desired requirements in terms of admissible peak load, as typically required by gait assistance, while guaranteeing low stiffness and a compact and lightweight design. This paper presents a novel compact monolithic torsional spring to be used as the basic component of a modular compliant system for series elastic actuators. The spring, whose design was refined through an iterative FEA-based optimization process, has an external diameter of 85mm, a thickness of 3mm and a weight of 61.5 g. The spring, characterized using a cus-tom dynamometric test bed, shows a linear torque versus angle characteristic. The com-pliant element has a stiffness of 98 N m=rad and it is capable of withstanding a maximum torque of 7:68 N m. A good agreement between simulated and experimental data were observed, with a maximum resultant error of 6%. By arranging a number of identical springs in series or in parallel, it is possible to render different torque versus angle characteristics, in order to match the specific applications requirements. [DOI: 10.1115/1.4007695

In order to derive maximum benefit from robotassisted rehabilitation, it is critical that the implemented control algorithms promote the participant's active engagement in therapy. Assist-as-needed (AAN) controllers address this need by providing only appropriate assistance during movement execution. Often, these controllers depend on the definition of an optimal movement profile, against which the participant's movements are compared. In this paper, we present a novel subject-adaptive controller, consisting of two main components: AAN control algorithm and online trajectory recalculation. First, the AAN control algorithm is based on an adaptive controller and introduces a novel feedback gain modification algorithm. Coupled with the uniformly ultimately bounded stability property of the resulting dynamic system, the developed controller is capable of changing the amount of error allowed during movement execution, while simultaneously estimating the forces provided by the participant that contribute to movement execution. Second, we present a real-time trajectory generation algorithm based on a physiologically optimal and experimentally validated asymmetric wrist movement profile. The feedback gain modification and trajectory generation algorithms are validated with the RiceWrist system in an experimental study involving five healthy subjects, with the modified AAN adaptive controller decreasing its feedback control action when a subject shifts his behavior from passively riding along with the robot during movement to actively engaging and initiating movements to the desired on-screen targets.