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SummaryWearable devices are fast evolving to address mobility and autonomy needs of elderly people who would benefit from physical assistance. Recent developments in soft robotics provide important opportunities to develop soft exoskeletons (also called exosuits) to enable both physical assistance and improved usability and acceptance for users. The XoSoft EU project has developed a modular soft lower limb exoskeleton to assist people with low mobility impairments. In this paper, we present the design of a soft modular lower limb exoskeleton to improve person’s mobility, contributing to independence and enhancing quality of life. The novelty of this work is the integration of quasi-passive elements in a soft exoskeleton. The exoskeleton provides mechanical assistance for subjects with low mobility impairments reducing energy requirements between 10% and 20%. Investigation of different control strategies based on gait segmentation and actuation elements is presented. A first hip–knee unilateral prototype is described, developed, and its performance assessed on a post-stroke patient for straight walking. The study presents an analysis of the human–exoskeleton energy patterns by way of the task-based biological power generation. The resultant assistance, in terms of power, was 10.9% ± 2.2% for hip actuation and 9.3% ± 3.5% for knee actuation. The control strategy improved the gait and postural patterns by increasing joint angles and foot clearance at specific phases of the walking cycle.

Motion analysis systems deliver quantitative information, e.g. on the progress of rehabilitation programs aimed at improving range of motion. Markerless systems are of interest for clinical application because they are low-cost and easy to use. The first generation of the Kinect™ sensor showed promising results in validity assessment compared to an established marker-based system. However, no literature is available on the validity of the new 'Kinect™ for Xbox one' (KinectOne) in tracking upper body motion. Consequently, this study was conducted to analyze the accuracy and reliability of the KinectOne in tracking upper body motion. Twenty subjects performed shoulder abduction in frontal and scapula plane, flexion, external rotation and horizontal flexion in two conditions (sitting and standing). Arm and trunk motion were analyzed using the KinectOne and compared to a marker-based system. Comparisons were made using Bland Altman statistics and Coefficient of Multiple Correlation. On average, differences between systems of 3.9±4.0° and 0.1±3.8° were found for arm and trunk motion, respectively. Correlation was higher for the arm than for the trunk motion. Based on the observed bias, the accuracy of the KinectOne was found to be adequate to measure arm motion in a clinical setting. Although trunk motion showed a very low absolute bias between the two systems, the KinectOne was not able to track small changes over time. Before the KinectOne can find clinical application, further research is required analyzing whether validity can be improved using a customized tracking algorithm or other sensor placement, and to analyze test-retest reliability.

One of the critical aspects in the design of an assistive wearable robot is the energy efficiency of the actuation system, since it affects significantly the weight and consequently the comfort of the system. Several strategies have been used in previous research, mostly based on energy harvesting, compliant elements for mechanical energy accumulation (springs or elastic cords), ratchets and clutches. However, the design of the optimal actuator arrangement is highly dependent on the task, which increases significantly the complexity of the design process. In this work we present an energy efficiency analysis and design optimization of an actuation system applied to a soft module lower limb exoskeleton. Instead of performing a comparison between predefined mechanism arrangements, we solve a full optimization problem which includes not only the mechanism parameters, but also the mechanism architecture itself. The optimization is performed for a walking task using gait data from a stroke subject, and the result is a set of actuator arrangements with optimal parameters for the analyzed task and selected user. The optimized mechanism is able to reduce the energy requirements by 20-65%, depending of the joint. The proposed mechanism is currently under development within the XoSoft EU project, a modular soft lower-limb exoskeleton to assist people with mobility impairments.

Although patients with NSCLBP seemed to produce a larger lumbar RE compared with healthy controls, study limitations render firm conclusions unsafe. Future studies should pay closer attention to power, precision, and reliability of the measurement approach, definition of outcome measures, and patient selection. We recommend a large, well-powered, prospective randomized control study that uses a standardized measurement approach and definitions for absolute error, CE, and variable error to address the hypothesis that proprioception may be impaired with CLBP.