An experimental characterization is presented for an improved version of a wearable assistive device for elbow motion. The design is revised with respect to requirements for elbow motion assistance, looking at applications both in rehabilitation therapies and exercising of elderly people. A laboratory prototype is built with lightweight, portable, easy-to-use features that are verified with test results, whose discussion is also provided as a characterization of operating performance.

The field of education has evolved significantly in recent years as it has incorporated new pedagogical methodologies. Many of these methodologies are designed to encourage students’ participation in the learning process. The traditional role of the student as a passive receiver of content is no longer considered valid. Teaching in mechanical engineering is no stranger to these changes either, where new learning activities have been designed to complement theory-heavy lectures. These activities take place in both physical and virtual laboratories. In case of the latter, the use of the GIM software (developed at the Department of Mechanical Engineering of the University of the Basque Country UPV/EHU, Spain) is a promising option. In this paper, features of the GIM that are most frequently used to support and exemplify the theoretical concepts taught in lectures are described using a case study. In addition, GIM is integrated into different learning activities to show its potential as a tool for learning and self-evaluation.

The high accuracy and dynamic performance of parallel robots (PRs) make them suitable to ensure safe operation in human–robot interaction. However, these advantages come at the expense of a reduced workspace and the possible appearance of type II singularities. The latter is due to the loss of control of the PR and requires further analysis to keep the stiffness of the PR even after a singular configuration is reached. All or a subset of the limbs could be responsible for a type II singularity, and they can be detected by using the angle between two output twist screws (OTSs). However, this angle has not been applied in control because it requires an accurate measure of the pose of the PR. This paper proposes a new hybrid controller to release a 4-DOF PR from a type II singularity based on a real time vision system. The vision system data are used to automatically readapt the configuration of the PR by moving the limbs identified by the angle between two OTSs. This controller is intended for a knee rehabilitation PR, and the results show how this release is accomplished with smooth controlled movements where the patient’s safety is not compromised.