Medical and rehabilitation exoskeletons are being increasingly considered by therapists when choosing a treatment for individuals affected by lower limb impairments. Although all such exoskeletons seem to provide similar features and performance, there are, in practice, significant differences among them in terms of maximum walking speed, maximum torque, weight, autonomy, interaction with the user, or even the way to use it. In this review, the state of the art of the main commercial exoskeletons is described, while analyzing their properties, advantages, and disadvantages. Three groups are considered: complete exoskeletons, partial exoskeletons and open lines of research. A comparative analysis between them is performed while considering the main scientific and technical aspects to be improved. In conclusion to this analysis, the balance between feasibility and innovation in exoskeletons development is a design challenge. Commercial exoskeletons must fulfil standards whilst ensuring their safety and robustness. However, achieving a new generation of exoskeletons means a need to implement new hardware paradigms, and to enhance control strategies focused on assist-as-needed scheme. Finally, some aspects to improve current designs of the exoskeleton are presented.

To analyse the versatility and adaptability of commercially available exoskeletons for mobility assistance and their adaptation to diverse pathologies through a review of clinical trials in robotic...

Current exoskeleton designs have opened new ways to therapists and patients for muscle maintenance and strength recovery therapy approaches. However, some issues remain to be solved. Lack of adaptation, versatility, or overweight are some of the main factors that should be improved. In this article, we present a novel design for a functional modular exoskeleton composed of four independent active joints using a decentralized electronic architecture, being the first wearable exoskeleton to apply this technology. This new approach avoids the use of a main processor, and the modular scheme allows every possible configuration between the hip and knee. The decentralized electronic architecture is enabled by implementing adaptive central pattern generator (CPG) algorithms in each module controller. Each CPG has been trained to mimic the joint trajectory of a healthy person walking. The communication between modules assures their coordination through synchronization terms. The operation of each configuration was first tested on a bench at different speeds and later used by a healthy subject. These tests show how the decentralized control strategy maintains the synchronization between modules, reproducing and adapting the trained walking pattern. These results prove that our proposal is suitable for the development of exoskeletons focused on personalized therapies.

Background and purpose: Stroke is one of the leading causes of disability in adults worldwide, and one of the main objectives in the rehabilitation of these patients is to recover the gait. New technologies have emerged to cope with this issue, complementing conventional therapy with the use of devices such as exoskeletons. The Marsi Active Knee (MAK) exoskeleton (Marsi Bionics SL, Madrid, Spain) has already been tested, but an updated version was improved to allow the patients to perform functional exercises. The aim of this study was to assess the safety and usability of the MAK in the stroke population as well as its potential clinical effects.Methods: A single‐group open label intervention trial was conducted. The device was used twice a week for 5 weeks during 1 h per visit. During the visits, sit‐to‐stand transitions, walking, stair climbing, trunk rotations, and weight‐transfer exercises were performed using the device. Adverse events were collected from participants and therapists to assess safety. The Quebec User Evaluation of the Satisfaction with assistive Technology (QUEST 2.0) was used by both therapists and participants to assess usability. To evaluate its clinical effects, active range of motion (ROM) and muscle strength were assessed in the lower limb.Results: Six participants with stroke were recruited. The device was shown to be safe since no serious adverse events were reported neither by patients nor by therapists. Every proposed exercise was performed. Regarding clinical effects, overall muscle strength showed an increase after the treatment, although ROM measurements did not show any difference.Discussion: Our results suggest that the MAK device is safe for stroke patients. Nevertheless, further changes to enhance usability are recommended, such as an improvement of the attachment system and an adaptation for the drop foot. Beneficial effects regarding increases in muscle strength were obtained. Further trials with a larger sample size, longer intervention periods, and a control group are needed to verify these results. Also, future research should focus on the usability of the MAK as an assistive technology.

Purpose: the purpose of this study was to evaluate the safety and usability of the ATLAS 2030 in children with Cerebral Palsy (CP) and Spinal Muscular Atrophy (SMA). Materials and Methods: the sample consisted of six children, three with CP and three with SMA, who received eight sessions of robot-assisted gait therapy. Safety was measured by the presence of adverse events. Usability was measured by spatiotemporal parameters, the Six-Minute Walking Test (6MWT), and the time needed for donning and doffing, as well as satisfaction questionnaires administered to therapists and patients. Results: no serious adverse events were reported. The average cadence and number of steps per session increased throughout sessions, as well as the distance covered in the 6MWT, both in participants with CP and SMA. The mean donning time at the end of the study was 4.6 ± 1.3 min, and only one therapist was necessary to carry out all of the sessions. Satisfaction was considered high by both children and therapists. Conclusions: the ATLAS 2030 was shown to be safe for children with CP and SMA. The usability of the device was good, since a progression in the spatiotemporal parameters was observed throughout the sessions, and patient and therapist satisfaction were high.

Bearing overheating and anomalous accelerations are two principal failure modes for this safety component. The supervision of bearing’s behaviour is essential to ensure a safe and reliable operation. A safety component’s failure may cause a speed limitation or even a non-available train for operating, so a predictive maintenance for bearings and other critical components is mandatory for the manufacturers, operators and maintainers in the railway sector. Bearing temperature, exterior temperature, train speed and other variables are measured every second in real time. From all the data collected and stored in the last years some algorithms and models are designed and trained in this paper to detect bearing anomalies 2 days before a real failure is detected and the safety alarm is enabled. The methodology for obtaining the optimal algorithm is exposed. Different artificial neural networks based on different optimization models such as the Mini-batch Gradient Descent (MGD) or Adam optimizer are compared. A final neural network with 10 hidden layers to detect bearing failure is proposed reaching 99% of accuracy, 95% of precision and 90% of sensitivity. The objective of predicting a bearing anomaly with some days in advanced is reached with high precision level, which will lead also to cost savings and a contribution for the sustainability because many inspections could be reduced and the energy cost associated to them.