Presentation_1_Passive Back Support Exoskeleton Improves Range of Motion Using Flexible Beams.PDF

<p>In the EU, lower back pain affects more than 40% of the working population. Mechanical loading of the lower back has been shown to be an important risk factor. Peak mechanical load can be reduced by ergonomic interventions, the use of cranes and, more recently, by the use of exoskeletons. Despite recent advances in the development of exoskeletons for industrial applications, they are not widely adopted by industry yet. Some of the challenges, which have to be overcome are a reduced range of motion, misalignment between the human anatomy and kinematics of the exoskeleton as well as discomfort. A body of research exists on how an exoskeleton can be designed to compensate for misalignment and thereby improve comfort. However, how to design an exoskeleton that achieves a similar range of motion as a human lumbar spine of up to 60° in the sagittal plane, has not been extensively investigated. We addressed this need by developing and testing a novel passive back support exoskeleton, including a mechanism comprised of flexible beams, which run in parallel to the spine, providing a large range of motion and lowering the peak torque requirements around the lumbo-sacral (L5/S1) joint. Furthermore, we ran a pilot study to test the biomechanical (N = 2) and functional (N = 3) impact on subjects while wearing the exoskeleton. The biomechanical testing was once performed with flexible beams as a back interface and once with a rigid structure. An increase of more than 25% range of motion of the trunk in the sagittal plane was observed by using the flexible beams. The pilot functional tests, which are compared to results from a previous study with the Laevo device, suggest, that the novel exoskeleton is perceived as less hindering in almost all tested tasks.</p

The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general