This paper details the design process and features of a novel upper limb rehabilitation exoskeleton named CLEVER (Compact, Low-weight, Ergonomic, Virtual/Augmented Reality Enhanced Rehabilitation) ARM. The research effort is focused on designing a lightweight and ergonomic upper-limb rehabilitation exoskeleton capable of producing diverse and perceptually rich training scenarios. To this end, the knowledge available in the literature of rehabilitation robotics is used along with formal conceptual design techniques. This paper briefly reviews the systematic approach used for design of the exoskeleton, and elaborates on the specific details of the proposed design concept and its advantages over other design possibilities. The kinematic structure of CLEVER ARM has eight degrees of freedom supporting the motion of shoulder girdle, glenohumeral joint, elbow and wrist. Six degrees of freedom of the exoskeleton are active, and the two degrees of freedom supporting the wrist motion are passive. Kinematics of the proposed design is studied analytically and experimentally with the aid of a 3D printed prototype. The paper is concluded by some remarks on the optimization of the design, motorization of device, and the fabrication challenges.

SummaryThis paper studies the problem of optimizing the kinematic structure of an eight degree-of-freedom upper-limb rehabilitation exoskeleton. The objective of optimization is achieving minimum volume and maximum dexterity in the workspace of daily activities specified by a set of upper-arm configurations. To formulate the problem, a new index is proposed for effective characterization of kinematic dexterity for wearable robots. Additionally, a set of constraints are defined to ensure that the optimal design can cover the desired workspace of the exoskeleton, while singular configurations and physical interferences are avoided. The formulated multi-objective optimization problem is solved using an evolutionary algorithm (Non-dominated Sorting Genetic Algorithm II) and the weighted sum approach. Among the resulted optimal points, the point with least sensitivity with respect to the variations of design variables is chosen as the final design.

This paper proposes a reference path generation method for upper-limb rehabilitation exoskeletons considering the scapulohumeral rhythms of the shoulder. The developed method is based on Central Nervous System's (CNS) governing rules for coordination of arm motions, and to the best of our knowledge is the first computational model to consider the motion of the inner shoulder in path generation. Existing reference generation methods which utilize computational models such as minimum jerk, minimum torque, etc, are based on the assumption that the shoulder joint does not move, and the origin of the reference frame is defined at the center of the glenohumeral (GH) joint. These computational methods are generally developed for simple point-to-point reaching movements with limited range of motion (RoM) which justifies the assumption of fixed shoulder center. However, most upper limb motions such as Activities of Daily Living (ADL) tasks include larger scale inward and outward reaching motions, during which the center of shoulder joint moves significantly. The proposed motion planning method can be used in upper-limb exoskeletons with 3 Degrees of Freedom (DoF) in shoulder and 1 DoF in elbow which are capable of supporting the motion of the shoulder girdle by moving the center of shoulder joint. The outputs of the proposed model are compared with the natural motion of arm during ADL tasks, recorded via a motion capture system. Comparison of the results show that the proposed model is able to reproduce human ADL motions, and can effectively be used for reference generation. The results of this study also confirm that neglecting the fine manipulations with wrist and fingers, ADL tasks can be modeled as large RoM reaching tasks from the perspective of elbow-shoulder coordination.

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