Unobtrusive, natural support control of an adaptive industrial exoskeleton using force myography.

Repetitive or tiring tasks and movements during manual work can lead to serious musculoskeletal disorders and, consequently, to monetary damage for both the worker and the employer. Among the most common of these tasks is overhead working while operating a heavy tool, such as drilling, painting, and decorating. In such scenarios, it is desirable to provide adaptive support in order to take some of the load off the shoulder joint as needed. However, even to this day, hardly any viable approaches have been tested, which could enable the user to control such assistive devices naturally and in real time. Here, we present and assess the adaptive Paexo Shoulder exoskeleton, an unobtrusive device explicitly designed for this kind of industrial scenario, which can provide a variable amount of support to the shoulders and arms of a user engaged in overhead work. The adaptive Paexo Shoulder exoskeleton is controlled through machine learning applied to force myography. The controller is able to determine the lifted mass and provide the required support in real time. Twelve subjects joined a user study comparing the Paexo driven through this adaptive control to the Paexo locked in a fixed level of support. The results showed that the machine learning algorithm can successfully adapt the level of assistance to the lifted mass. Specifically, adaptive assistance can sensibly reduce the muscle activity's sensitivity to the lifted mass, with an observed relative reduction of up to 31% of the muscular activity observed when lifting 2 kg normalized by the baseline when lifting no mass.

Assessing the efficiency of exoskeletons in physical strain reduction by biomechanical simulation with AnyBody Modeling System.

Introduction: Recently, many industrial exoskeletons for supporting workers in heavy physical tasks have been developed. However, the efficiency of exoskeletons with regard to physical strain reduction has not been fully proved, yet. Several laboratory and field studies have been conducted, but still more data, that cannot be obtained solely by behavioral experiments, are needed to investigate effects on the human body. Methods: This paper presents an approach to extend laboratory and field research with biomechanical simulations using the AnyBody Modeling System. Based on a dataset recorded in a laboratory experiment with 12 participants using the exoskeleton Paexo Shoulder in an overhead task, the same situation was reproduced in a virtual environment and analyzed with biomechanical simulation. Results: Simulation results indicate that the exoskeleton substantially reduces muscle activity and joint reaction forces in relevant body areas. Deltoid muscle activity and glenohumeral joint forces in the shoulder were decreased between 54 and 87%. Simultanously, no increases of muscle activity and forces in other body areas were observed. Discussion: This study demonstrates how a simulation framework could be used to evaluate changes in internal body loads as a result of wearing exoskeletons. Biomechanical simulation results widely agree with experimental measurements in the previous laboratory experiment and supplement such by providing an insight into effects on the human musculoskeletal system. They confirm that Paexo Shoulder is an effective device to reduce physical strain in overhead tasks. The framework can be extended with further parameters, allowing investigations for product design and evaluation.

Objective and Subjective Effects of a Passive Exoskeleton on Overhead Work.

Overhead work is a frequent cause of shoulder work-related musculoskeletal disorders. Exoskeletons offering arm support have the potential to reduce shoulder strain, without requiring large scale reorganization of the workspace. Assessment of such systems however requires to take multiple factors into consideration. This paper presents a thorough in-lab assessment of PAEXO, a novel passive exoskeleton for arm support during overhead work. A list of evaluation criteria and associated performance metrics is proposed to cover both objective and subjective effects of the exoskeleton, on the user and on the task being performed. These metrics are measured during a lab study, where 12 participants perform an overhead pointing task with and without the exoskeleton, while their physical, physiological and psychological states are monitored. Results show that using PAEXO reduces shoulder physical strain as well as global physiological strain, without increasing low back strain nor degrading balance. These positive effects are achieved without degrading task performance. Importantly, participants' opinions of PAEXO are positive, in agreement with the objective measures. Thus, PAEXO seems a promising solution to help prevent shoulder injuries and diseases among overhead workers, without negatively impacting productivity.

Biomechanical and Metabolic Effectiveness of an Industrial Exoskeleton for Overhead Work.

Overhead work activities can lead to shoulder pain and serious musculoskeletal disorders (WMSD), such as rotator cuff injury and degeneration. Recently developed exoskeletons show promising results in supporting workers in such activities. In this study, a novel exoskeleton was investigated for two different overhead tasks with twelve participants. To investigate the effects of the device, electromyographic (EMG) signals of different shoulder and adjacent muscles as well as kinematic and metabolic parameters were analyzed with and without the exoskeleton. The mean EMG amplitude of all evaluated muscles was significantly reduced when the exoskeleton was used for the overhead tasks. This was accompanied by a reduction in both heart rate and oxygen rate. The kinematic analysis revealed small changes in the joint positions during the tasks. This study demonstrated the biomechanical and metabolic benefits of an exoskeleton designed to support overhead work activities. The results suggest improved physiological conditions and an unloading effect on the shoulder joint and muscles which are promising indicators that the exoskeleton may be a good solution to reduce shoulder WMSD among workers who carry out overhead tasks on a regular basis.

Estimating the L5S1 flexion/extension moment in symmetrical lifting using a simplified ambulatory measurement system.

Mechanical loading of the spine has been shown to be an important risk factor for the development of low-back pain. Inertial motion capture (IMC) systems might allow measuring lumbar moments in realistic working conditions, and thus support evaluation of measures to reduce mechanical loading. As the number of sensors limits applicability, the objective of this study was to investigate the effect of the number of sensors on estimates of L5S1 moments. Hand forces, ground reaction forces (GRF) and full-body kinematics were measured using a gold standard (GS) laboratory setup. In the ambulatory setup, hand forces were estimated based on the force plates measured GRF and body kinematics that were measured using (subsets of) an IMC system. Using top-down inverse dynamics, L5S1 flexion/extension moments were calculated. RMSerrors (Nm) were lowest (16.6) with the full set of 17 sensors and increased to 20.5, 22 and 30.6, for 8, 6 and 4 sensors. Absolute errors in peak moments (Nm) ranged from 17.7 to 16.4, 16.9 and 49.3 Nm, for IMC setup's with 17, 8, 6 and 4 sensors, respectively. When horizontal GRF were neglected for 6 sensors, RMSerrors and peak moment errors decreased from 22 to 17.3 and from 16.9 to 13 Nm, respectively. In conclusion, while reasonable moment estimates can be obtained with 6 sensors, omitting the forearm sensors led to unacceptable errors. Furthermore, vertical GRF information is sufficient to estimate L5S1 moments in lifting.