In this paper, as a preliminary study, we show that accuracy and repeatability in ambulatory measurements of wrist joint are related to movement conditions which are going to be used in a calibration procedure. We chose two representative in-vivo, non-invasive calibration methods of the human upper limb, from those available in literature, to estimate joint parameters. Developing an analytical model of wrist joint we used sets of synthetic data each of which containing different number of samples, joint covariations and noise to estimate the repeatability and accuracy of the methods in estimation. Afterwards, we used our mechanical mock-up to examine single joint motions as well as the rotation of both joints (i.e. flexion-extension rotation and radial-ulnar deviation) on accuracy and repeatability by calculating the mean and standard deviation of the relative errors. Finally, we show that the accuracy of adapted method (its relative error was less than 7%) is better than the other method in estimating the joint parameters.
This work focuses on anthropomorphic exoskeletons for the human wrist. We consider a 2 dof model for the human wrist with non intersecting joints and a similar model for the exoskeleton. We assume a viscoelastic attachment between the human hand and the handle of the exoskeleton which on one side allows the different kinematics of the exoskeleton to follow the human wrist and, on the other side, induces reaction forces at all joints, in particular causing discomfort. We quantify discomfort as the amount of potential energy stored in the deformation of the viscoelastic attachment.For a specific exoskeleton implementation, based on kinematic simulations, we report the kinematic mismatch (i.e. differences between the human joints and the corresponding exoskeleton joints) as well as the reaction forces arising when the human joints assume postures throughout their physiological range of motion. Considering a typical distribution of joint offset for humans (derived from literature) and the asymmetry in the discomfort function (derived from our simulations) we address the 'one-size-fits-all' problem and propose an optimal joint offset for the exoskeleton, based on the minimization of the aggregate loss function.
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