Functional Analysis of Upper-Limb Movements in the Cartesian Domain

Abstract

The characterization of human upper limb kinematics is fundamental not only in neuroscience and clinical practice, but also for the planning of human-like robot motions in rehabilitation and assistive robotics. One promising approach to endow anthropomorphic robotic manipulators with human motion characteristics is to directly embed human upper limb principal motion modes at joint level, which are computed through functional analysis, in the robot trajectory optimization. This planning method poses some challenges when the kinematics of the manipulator is different from the model used for human data acquisition. In a previous work, we proposed to tackle this issue by mapping human trajectories onto robotic systems relying on Cartesian impedance control. An alternative method could move from the application of the functional analysis to human upper limb kinematics, working directly in the Cartesian domain. In this work, we present the results of this characterization on the data from 33 healthy subjects during the execution of daily-living activities. We found statistical differences between the amount of variability explained by a given number of basis elements in different directions of the Cartesian space. This suggests that some directions of the space are associated with a more complex motion evolution with respect to others, opening interesting perspectives for robot planning, neuroscience and human motion control.

This work was partially supported by the EU H2020 project “SoftPro” (no. 688857) “SOPHIA” (no. 871237), by the European Research Council (ERC) under Grant 810346 (Natural BionicS), and by the Italian Ministry of Education and Research (MIUR) in the framework of the CrossLab project (Departments of Excellence). These authors equally contributed to this work.