Exoskeleton Research Articles

Enhancing Personalized Rehabilitation: Integrating Assist-as-Needed System With Real-Time Feedback

Abstract Conventional rehabilitation programs often lack precise real-time feedback, leading to varied training results at different centers. To address this, personalized rehabilitation strategies have been developed using robotic technologies and exoskeletons with assist-as-needed (AAN) controllers to improve recovery rates for individuals with stroke and neuromuscular disorders. This research introduces an automated therapy approach with a patient-specific AAN support strategy that provides immediate feedback, enhancing the rehabilitation process. The system uses minimal data to create effective personalized models and integrates sensors and algorithms for continuous monitoring, improving the efficacy of therapy. Initial trials with an exoskeleton that focused on elbow movements showed promising results in adjusting support in real-time and providing personalized interventions through torque-controlled motors. This system assesses impairment levels, visualizes motor energy needs, and helps design customized rehabilitation programs, significantly enhancing therapeutic results.

Antibacterial and Cell-Viability of Hydroxyapatite Derived from Waste Marine Shell for Biomedical Applications

The present study discusses on the functional groups, structural characterization and thermal behaviour of Crassostrea angulata shell used for the synthesis of a biocompatible hydroxyapatite material. The hydroxyapatite was synthesized from C. angulata shell through precipitation method and characterized using XRD, FTIR, FE-SEM, EDX mapping, HR-TEM and SAED pattern. The formation of hydroxyapatite was confirmed from the high intense X-ray diffraction lines and by the presence of chemical groups such as PO43–, OH– and CO32–. The structural changes during the formation of hydroxyapatite from the thermal decomposition of C. angulata shell were studied through XRD and TG-DTA. The morphology study by FE-SEM indicates that the synthesized hydroxyapatite materials were in the form of clusters of rod-like particles. The SAED patterns and XRD spectral lines confirmed the crystalline nature of the synthesized hydroxyapatite. The antibacterial activity and cell viability assay of prepared hydroxyapatite were studied to assess its suitability in various biomedical applications. The antibacterial activity of hydroxyapatite was assessed against Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus saprophyticus) bacterial strains. The cytocompatibility of hydroxyapatite was assessed through an MTT assay using osteoblast cells (MG-63 cell). Thus, the prepared hydroxyapatite shows good antibacterial action and cell viability nature and it can be applied in various biomedical applications.

Optimal Design of a Bilateral Stand-Alone Robotic Motion-Assisted Finger Exoskeleton for Home Rehabilitation

This paper presents a novel exoskeleton robot that can be used at home to rehabilitate the index fingers of stroke-affected patients. This exoskeleton is designed as a one-degree-of-freedom four-bar mechanism able to guide the human index finger to perform a finger curl exercise motion. The proposed device is the only lateral, stand-alone mechanism built to date that can carry the weight of the human hand, thus making the user free from wearing it. The design starts by tracing the trajectory of the index finger using ‘Angulus’ software. ‘SALAR Mechanism Synthesizer’ software is used for dimensional synthesis of the four-bar mechanism. Using additive manufacturing technology, a prototype of the proposed device is developed. Static force analysis is performed to select the most appropriate actuator for producing the required torque to manipulate the fingers effectively. The kinematics of the index finger while performing a finger curl exercise is obtained. The proposed linkage mechanism can drive the index fingers of both hands. Simulation and experimental results proved the feasibility and effectiveness of the proposed design to be used for index finger rehabilitation for a wide range of users and applications by making simple minor alterations in the design. Also, a scheme for when the device can be used for rehabilitating the middle finger together with the index finger when performing flexion and extension motions is discussed.

The effects of soft vs. rigid back-support exoskeletons on trunk dynamic stability and trunk-pelvis coordination in young and old adults during repetitive lifting

While back-support exoskeletons are increasing in popularity as an ergonomic intervention for manual material handling, they may cause alterations to neuromuscular control required for maintaining spinal stability. This study evaluated the effects of soft and rigid passive exoskeletons on trunk local dynamic stability and trunk-pelvis coordination. Thiry-two young (18–30 years) and old (45–60 years) men and women completed repetitive lifting and lowering tasks using two different exoskeletons and in a control condition. Both exoskeletons significantly reduced the short-term maximum Lyapunov exponent (LyE) of the trunk (p < 0.01), suggesting improved local dynamic stability. There was also a significant main effect of age (p = 0.05): older adults exhibited lower short-term LyE that young adults. Use of the soft exoskeleton significantly increased, while the rigid exoskeleton significantly decreased, long-term LyE, and these changes were more pronounced in the young group compared to the old group. Additionally, exoskeleton use resulted in significant increase (p < 0.001) of mean absolute relative phase (MARP) and deviation phase (DP) by ∼30–60 %, with greater increases due to the rigid than the soft device. Thus, trunk-pelvic coordination and coordination variability were negatively impacted by exoskeleton use. Potential reasons for these findings may include exoskeleton-induced changes in lifting strategy, reduced peak trunk flexion velocity, and cycle-to-cycle variability of trunk velocity. Furthermore, although the soft and rigid devices caused comparable changes in trunk-extensor muscle activity, they exhibited differential effects on long-term maximum Lyapunov exponents as well as trunk-pelvic coordination, indicating that exoskeleton design features can have complex effects on trunk neuromuscular control.

A versatile knee exoskeleton mitigates quadriceps fatigue in lifting, lowering, and carrying tasks.

The quadriceps are particularly susceptible to fatigue during repetitive lifting, lowering, and carrying (LLC), affecting worker performance, posture, and ultimately lower-back injury risk. Although robotic exoskeletons have been developed and optimized for specific use cases like lifting-lowering, their controllers lack the versatility or customizability to target critical muscles across many fatiguing tasks. Here, we present a task-adaptive knee exoskeleton controller that automatically modulates virtual springs, dampers, and gravity and inertia compensation to assist squatting, level walking, and ramp and stairs ascent/descent. Unlike end-to-end neural networks, the controller is composed of predictable, bounded components with interpretable parameters that are amenable to data-driven optimization for biomimetic assistance and subsequent application-specific tuning, for example, maximizing quadriceps assistance over multiterrain LLC. When deployed on a backdrivable knee exoskeleton, the assistance torques holistically reduced quadriceps effort across multiterrain LLC tasks (significantly except for level walking) in 10 human users without user-specific calibration. The exoskeleton also significantly improved fatigue-induced deficits in time-based performance and posture during repetitive lifting-lowering. Last, the system facilitated seamless task transitions and garnered a high effectiveness rating postfatigue over a multiterrain circuit. These findings indicate that this versatile control framework can target critical muscles across multiple tasks, specifically mitigating quadriceps fatigue and its deleterious effects.

Fractional‐order fixed‐time sliding mode control of robotic manipulators with robust exact differentiator

AbstractThis paper introduces a robust position tracking control structure of exoskeleton robots (ERs). An open environment and body flexibility are the main challenges in ER control system design. First, a fractional‐order nonsingular terminal sliding mode (FONTSM) controller is proposed for a robotic manipulator with uncertainty, where lumped unknown dynamics are computed by time‐delay estimation (TDE). Secondly, a robust exact differentiator (RED) is employed as the output feedback observer for the velocity sensorless robotic system. Thirdly, the stability of the FONTSM control system is demonstrated. It is proved that the system error can move to the specified value along the sliding mode surface at a fixed time and can reach the sliding mode surface after a finite time. Finally, simulations on a 2‐DOF robotic manipulator show the effectiveness of the fixed‐time control strategies. When a combined trigonometric function disturbance is applied, the joint angle error is reduced to 1% by the model‐free controller based on output feedback within approximately 1 s.

Passage and removal of the Amundsen Gulf Ice Stream, NW Laurentide Ice Sheet, recorded by the glacial and sea level history of southern Banks Island, Arctic Canada

Earlier reconstructions of the glacial history of the western Canadian Arctic Archipelago, commonly portrayed Banks Island as an ice-free biological refugium during the Last Glacial Maximum, ostensibly constituting the northeast extremity of Beringia. This has now been contradicted by widespread fieldwork across the northern and western coasts documenting their inundation by the northwest Laurentide Ice Sheet that extended onto the polar continental shelf. Here we report the surficial geology and deglacial sea levels across southern Banks Island completing the island-wide evidence for a pervasive ice cover during the Late Wisconsinan.Moraines and erratics confirm the passage of an ice stream at least 1.1 km thick through Amundsen Gulf that onlapped the south coast of the island. The inland margin of the ice stream is marked by a prominent 80 km long shear moraine (Sachs moraine) that contacted thin, cold-based Laurentide ice crossing the island's interior. Subsequent thinning and retreat of the Amundsen Gulf Ice Stream from the Sachs moraine occurred in concert with its separation from topographically-confined ice lobes in the interior recorded by prominent ice-marginal meltwater channels. As the ice stream retreated offshore, a prominent kettled outwash plain was deposited along the coast marking marine limit at 20 m asl. From an unknown position offshore, the ice stream readvanced deforming the south shore of the kettled lowland marked by the 40 km long ‘Sand Hills moraine’. Based on updated field mapping, the 'Sand Hills moraine' is now recognized as the westward extension of the more widespread Jesse moraine belt.Deglacial marine limit rises eastward across the island from 11 to 40 m asl, bordering Prince of Wales Strait. Marine limit and all lower shorelines across the island's south coast (for ∼ 200 km) are barren of marine shells. This is because sea level had regressed from marine limit to a lowstand offshore before Pacific molluscs recolonized the western Canadian Arctic at 13.7 cal ka BP, their entry occasioned by the resubmergence of Bering Strait. This requires that the breakup of the western Amundsen Gulf Ice Stream (including the M'Clure Strait Ice Stream along northern Banks Island) occurred before 14 cal ka BP, documenting that the NW Laurentide Ice Sheet must have contributed to Meltwater-Pulse-1A. Although the retreat from the outermost parts of the Jesse moraine belt also pre-date the arrival of shells, we show that the youngest (central) segment along eastern Amundsen Gulf dates to ∼12.9 cal ka BP, documenting that the Jesse moraine belt is highly time transgressive (spanning >13.7 to 12.9 cal ka BP). Radiocarbon dates on woody plants and bryophytes demonstrate that the island was biologically viable as early as 12.6 cal ka BP and that all coastlines were submergent soon afterwards and remain so today.

A lightweight passive ankle exoskeleton adjusted stiffness by shape memory alloy

Purpose The purpose of this paper is to actively calibrate power density to match the application requirements with as small an actuator as possible. So, this paper introduces shape memory alloy to design variable stiffness elements. Meanwhile, the purpose of this paper is also to solve the problem of not being able to install sensors on shape memory alloy due to volume limitations. Design/methodology/approach This paper introduces the design, modeling and control process for a variable stiffness passive ankle exoskeleton, adjusting joint stiffness using shape memory alloy (SMA). This innovative exoskeleton aids the human ankle by adapting the precompression of elastic components by SMA, thereby adjusting the ankle exoskeleton’s integral stiffness. At the same time, this paper constructs a mathematical model of SMA to achieve a dynamic stiffness adjustment function. Findings Using SMA as the driving force for stiffness modification in passive exoskeletons introduces several distinct advantages, inclusive of high energy density, programmability, rapid response time and simplified structural design. In the course of experimental validation, this ankle exoskeleton, endowed with variable stiffness, proficiently executed actions like squatting and walking and it can effectively increase the joint stiffness by 0.2 Nm/Deg. Originality/value The contribution of this paper is to introduce SMA to adjust the stiffness to actively calibrate power density to match the application requirements. At the same time, this paper constructs a mathematical model of SMA to achieve a dynamic stiffness adjustment function.

Hybrid-3D robotic suite in spine and trauma surgery - experiences in 210 patients

BackgroundIn modern Hybrid ORs, the synergies of navigation and robotics are assumed to contribute to the optimisation of the treatment in trauma, orthopaedic and spine surgery. Despite promising evidence in the area of navigation and robotics, previous publications have not definitively proven the potential benefits. Therefore, the aim of this retrospective study was to evaluate the potential benefit and clinical outcome of patients treated in a fully equipped 3D-Navigation Hybrid OR.MethodsProspective data was collected (March 2022- March 2024) after implementation of a fully equipped 3D-Navigation Hybrid OR (“Robotic Suite”) in the authors level 1 trauma centre. The OR includes a navigation unit, a cone beam CT (CBCT), a robotic arm and mixed reality glasses. Surgeries with different indications of the spine, the pelvis (pelvic ring and acetabulum) and the extremities were performed. Spinal and non-spinal screws were inserted. The collected data was analysed retrospectively. Pedicle screw accuracy was graded according to the Gertzbein and Robbins (GR) classification.ResultsA total of n = 210 patients (118 m:92f) were treated in our 3D-Navigation Hybrid OR, with 1171 screws inserted. Among these patients, 23 patients (11.0%) arrived at the hospital via the trauma room with an average Injury Severity Score (ISS) of 25.7. There were 1035 (88.4%) spinal screws inserted at an accuracy rate of 98.7% (CI95%: 98.1-99.4%; 911 GR-A & 111 GR-B screws). The number of non-spinal screws were 136 (11.6%) with an accuracy rate of 99.3% (CI95%: 97.8-100.0%; 135 correctly placed screws). This resulted in an overall accuracy rate of 98.8% (CI95%: 98.2-99.4%). The robotic arm was used in 152 cases (72.4%), minimally invasive surgery (MIS) was performed in 139 cases (66.2%) and wound infection occurred in 4 cases (1,9%). Overall, no revisions were needed.ConclusionBy extending the scope of application, this study showed that interventions in a fully equipped 3D-Navigation Hybrid OR can be successfully performed not only on the spine, but also on the pelvis and extremities. In trauma, orthopaedics and spinal surgery, navigation and robotics can be used to perform operations with a high degree of precision, increased safety, reduced radiation exposure for the OR-team and a very low complication rate.

How Effective Are Forecasting Models in Predicting Effects of Exoskeletons on Fatigue Progression?

Forecasting can be utilized to predict future trends in physiological demands, which can be beneficial for developing effective interventions. This study implemented forecasting models to predict fatigue level progression when performing exoskeleton (EXO)-assisted tasks. Specifically, perceived and muscle activity data were utilized from nine recruited participants who performed 45° trunk flexion tasks intermittently with and without assistance until they reached medium-high exertion in the low-back region. Two forecasting algorithms, Autoregressive Integrated Moving Average (ARIMA) and Facebook Prophet, were implemented using perceived fatigue levels alone, and with external features of low-back muscle activity. Findings showed that univariate models without external features performed better with the Prophet model having the lowest mean (SD) of root mean squared error (RMSE) across participants of 0.62 (0.24) and 0.67 (0.29) with and without EXO-assisted tasks, respectively. Temporal effects of BSIE on delaying fatigue progression were then evaluated by forecasting back fatigue up to 20 trials. The slope of fatigue progression for 20 trials without assistance was ~48-52% higher vs. with assistance. Median benefits of 54% and 43% were observed for ARIMA (with external features) and Prophet algorithms, respectively. This study demonstrates some potential applications for forecasting models for workforce health monitoring, intervention assessment, and injury prevention.

Developing a real-time hand exoskeleton system that controlled by a hand gesture recognition system via wireless sensors

Numerous studies have been conducted using wearable sensors on gesture recognition and classification methods for the control of robotic arms, prostheses, and exoskeleton systems. The primary goal of this study is to classify 32 different hand gestures in real-time using electromyography (EMG) signals. EMG signals obtained by measuring the electrical activity of the muscles were simulated wirelessly on a hand exoskeleton. A Myo Armband placed on the upper arm was used to generate these signals for evaluating and validating the system. The signals were normalized according to maximum voluntary contraction (MVC), and relevant features such as MAV, STD, VAR, RMS, IEMG, ZC, and WL were selected using the univariate feature selection. A support vector machine (SVM) was then used for classification. The 32 different hand gestures were classified to an accuracy level of 99.9%. In short, this proposed approach can be effectively used in real-time hand gesture recognition and generating real-time actions for the hand exoskeleton system.

Integration of multiscale fusion of residual neural network with 2-D gramian angular fields for lower limb movement recognition based on multi-channel sEMG signals

The human lower limb movements recognition (LLMR) plays a pivotal role in active lower limb exoskeleton robots. Employing surface electromyography (sEMG) signals for LLMR allows for the convenient, rapid and stable capture of signal variations, facilitating efficient identification of lower limb motion patterns. However, current sEMG-based LLMR methods face challenges such as incomplete feature extraction, limited contextual information and restricted feature extraction scales during feature extraction. This paper proposed a LLMR method based on Gramian Angular Fields (GAF) and multiscale fusion of Residual Neural Network (MS-ResNet). The denoised sEMG time series was transformed into Gramian Angular Difference Field (GADF) matrix based on GAF. The MS-ResNet model, incorporating ResNet and multiscale feature fusion concepts, was proposed to comprehensively capture global and local information through different-scale feature extraction and fusion, so as to improve recognition performance. sEMG signals from 11 muscles of the preferred leg of 15 healthy subjects were recorded during six common lower limb movements. Experimental analysis investigated the impact of the convolutional kernel size (k × k) in Stream 2 of MS-ResNet and the number of muscles involved on recognition performance. The study revealed that selecting k as 13, coupled with 11 muscles, yielded optimal model performance with the average cross-individual recognition accuracy reaching 97.62 %, demonstrating the model’s efficiency in LLMR. This method could provide a viable solution for developing more efficient and reliable LLMR systems, applicable to lower limb exoskeleton robots and intelligent prosthetics.

Exploring microbial diversity in the rhizosphere: a comprehensive review of metagenomic approaches and their applications.

The rhizosphere, the soil region influenced by plant roots, represents a dynamic microenvironment where intricate interactions between plants and microorganisms shape soil health, nutrient cycling, and plant growth. Soil microorganisms are integral players in the transformation of materials, the dynamics of energy flows, and the intricate cycles of biogeochemistry. Considerable research has been dedicated to investigating the abundance, diversity, and intricacies of interactions among different microbes, as well as the relationships between plants and microbes present in the rhizosphere. Metagenomics, a powerful suite of techniques, has emerged as a transformative tool for dissecting the genetic repertoire of complex microbial communities inhabiting the rhizosphere. The review systematically navigates through various metagenomic approaches, ranging from shotgun metagenomics, enabling unbiased analysis of entire microbial genomes, to targeted sequencing of the 16S rRNA gene for taxonomic profiling. Each approach's strengths and limitations are critically evaluated, providing researchers with a nuanced understanding of their applicability in different research contexts. A central focus of the review lies in the practical applications of rhizosphere metagenomics in various fields including agriculture. By decoding the genomic content of rhizospheric microbes, researchers gain insights into their functional roles in nutrient acquisition, disease suppression, and overall plant health. The review also addresses the broader implications of metagenomic studies in advancing our understanding of microbial diversity and community dynamics in the rhizosphere. It serves as a comprehensive guide for researchers, agronomists, and policymakers, offering a roadmap for harnessing metagenomic approaches to unlock the full potential of the rhizosphere microbiome in promoting sustainable agriculture.

Digital Technology in Healthcare—An Ethical Overview

This overview of ethical aspects of artificial intelligence (AI) in healthcare is organized according to major types of medical activities. It discusses important ethical problems in (1) diagnostic uses of AI such as image interpretation and text interpretation, (2) the use of AI as decision support or even as decision-maker, (3) its use for treatment, for instance in robotic surgery, exoskeletons, virtual psychotherapy and therapeutic robots (care robots), and (4) the use of AI for healthcare documentation and communication. Summing up, we emphasize two major challenges in the introduction of AI that should concern not only healthcare professionals but also higher level decision-makers such as politicians and hospital directors. The first of these is the need to retain human contacts between patients and healthcare, in particular contacts that are conducive to patient health and well-being. The second is the need to ensure that the introduction of AI in healthcare does not create or exacerbate injustices in healthcare. This can happen if prevalent human biases are encoded in AI tools. It can also occur if people with less money have to use inexpensive AI tools such as virtual psychotherapists whereas the well-to-do have access to a human psychotherapist. On the other hand, AI tools can be used to provide better healthcare to all who need it, and they can also be programmed to avoid biases and other mistakes that humans are prone to. The article concludes with brief summaries of the articles in the special issue on AI in healthcare that it introduces.

Exoskeletal-Assisted Walking in Veterans With Paralysis: A Randomized Clinical Trial.

Robotic exoskeletons leverage technology that assists people with spinal cord injury (SCI) to walk. The efficacy of home and community exoskeletal use has not been studied in a randomized clinical trial (RCT). To examine whether use of a wheelchair plus an exoskeleton compared with use of only a wheelchair led to clinically meaningful net improvements in patient-reported outcomes for mental and physical health. This RCT of veterans with SCI was conducted at 15 Veterans Affairs medical centers in the US from September 6, 2016, to September 27, 2021. Data analysis was performed from March 10, 2022, to June 20, 2024. Participants were randomized (1:1) to standard of care (SOC) wheelchair use or SOC plus at-will use of a US Food and Drug Administration (FDA)-cleared exoskeletal-assisted walking (EAW) device for 4 months in the home and community. Two primary outcomes were studied: 4.0-point or greater improvement in the mental component summary score on the Veterans RAND 36-Item Health Survey (MCS/VR-36) and 10% improvement in the total T score of the Spinal Cord Injury-Quality of Life (SCI-QOL) physical and medical health domain and reported as the proportion who achieved clinically meaningful changes. The primary outcomes were measured at baseline, post randomization after advanced EAW training sessions, and at 2 months and 4 months (primary end point) in the intervention period. Device usage, reasons for not using, and adverse events were collected. A total of 161 veterans with SCI were randomized to the EAW (n = 78) or SOC (n = 83) group; 151 (94%) were male, the median age was 47 (IQR, 35-56) years, and median time since SCI was 7.3 (IQR, 0.5 to 46.5) years. The difference in proportion of successes between the EAW and SOC groups on the MCS/VR-36 (12 of 78 [15.4%] vs 14 of 83 [16.9%]; relative risk, 0.91; 95% CI, 0.45-1.85) and SCI-QOL physical and medical health domain (10 of 78 [12.8%] vs 11 of 83 [13.3%]; relative risk, 0.97; 95% CI, 0.44-2.15) was not statistically different. Device use was lower than expected (mean [SD] distance, 1.53 [0.02] miles per month), primarily due to the FDA-mandated companion being unavailable 43.9% of the time (177 of 403 instances). Two EAW-related foot fractures and 9 unrelated fractures (mostly during wheelchair transfers) were reported. In this RCT of veterans with SCI, the lack of improved outcomes with EAW device use may have been related to the relatively low device usage. Solutions for companion requirements and user-friendly technological adaptations should be considered for improved personal use of these devices. ClinicalTrials.gov Identifier: NCT02658656.

Adaptive Modular Neural Control for Online Gait Synchronization and Adaptation of an Assistive Lower-Limb Exoskeleton.

Gait synchronization has attracted significant attention in research on assistive lower-limb exoskeletons because it can circumvent conflicting movements and improve the assistance performance. This study proposes an adaptive modular neural control (AMNC) for online gait synchronization and the adaptation of a lower-limb exoskeleton. The AMNC comprises several distributed and interpretable neural modules that interact with each other to effectively exploit neural dynamics and adopt feedback signals to quickly reduce the tracking error, thereby smoothly synchronizing the exoskeleton movement with the user's movement on the fly. Taking state-of-the-art control as the benchmark, the proposed AMNC provides further improvements in the locomotion phase, frequency, and shape adaptation. Accordingly, under the physical interaction between the user and the exoskeleton, the control can reduce the optimized tracking error and unseen interaction torque by up to 80% and 30%, respectively. Accordingly, this study contributes to the advancement of exoskeleton and wearable robotics research in gait assistance for the next generation of personalized healthcare.

Training and Familiarization with Industrial Exoskeletons: A Review of Considerations, Protocols, and Approaches for Effective Implementation.

Effective training programs are essential for safely integrating exoskeletons (EXOs) in industrial workplaces. Since the effects of wearable systems depend highly upon their proper use, lack of training of end-users may cause adverse effects on users. We reviewed articles that incorporated training and familiarization protocols to train novices on proper operation/use of EXOs. Findings showed variation in training methods that were implemented to train study participants in EXO evaluation studies. Studies also indicate that multiple (up to four) sessions may be needed for novice EXO wearers to match movement patterns of experts, and training can offer benefits in enhancing motor learning in novices. Biomechanical assessments and ergonomic evaluations can be helpful in developing EXO-specific training protocols by determining training parameters (duration/number of sessions and task difficulty). Future directions include development of personalized training approaches by assessing user behavior/performance through integration of emerging sensing technologies. Application of simulators and use of data-driven approaches for customizing training protocols to individuals, tasks, and EXO design are provided along with a comprehensive training framework. Discussed elements in this article can be helpful to exoskeleton researchers in familiarizing novice users to EXOs prior to evaluation, and to practitioners in developing protocols for training workforce.

Development of an individualized stable and force-reducing lower-limb exoskeleton

In this study, an individualized and stable passive-control lower-limb exoskeleton robot was developed. Users’ joint angles and the center of pressure (CoP) of one of their soles were input into a convolutional neural network (CNN)–long short-term memory (LSTM) model to evaluate and adjust the exoskeleton control scheme. The CNN–LSTM model predicted the fitness of the control scheme and output the results to the exoskeleton robot, which modified its control parameters accordingly to enhance walking stability. The sole’s CoP had similar trends during normal walking and passive walking with the developed exoskeleton; the y-coordinates of the CoPs with and without the exoskeleton had a correlation of 91%. Moreover, electromyography signals from the rectus femoris muscle revealed that it exerted 40% less force when walking with a stable stride length in the developed system than when walking with an unstable stride length. Therefore, the developed lower-limb exoskeleton can be used to assist users in achieving balanced and stable walking with reduced force application. In the future, this exoskeleton can be used by patients with stroke and lower-limb weakness to achieve stable walking.

Design, simulation, and experimental evaluation of a light weight, and wearable cable driven ForeWrist exoskeleton robot for assistance and rehabilitation

Design, simulation, and experimental evaluation of a light weight, and wearable cable driven ForeWrist exoskeleton robot for assistance and rehabilitation

The effects of working with a passive arm-support exoskeleton on objective and self-reported measures during field tasks – a randomised cross-over study

Musculoskeletal disorders (MSDs) are prevalent under poor working situations. Where it is not possible to remove the root cause of MSDs, passive exoskeletons could be a solution. In this randomised cross-over field study we investigated the effect of a passive arm-support exoskeleton. Ten participants, recruited from a Dutch gas company, were measured with and without exoskeleton assessing muscle activity, heart rate (HR), arm elevation, and reported about their experiences. Participants spent more time in high arm elevation levels with the exoskeleton than without. Muscle activity was lower in the trapezius (Beta: −1.8 [−3.1; −0.4]) and deltoid (Beta: −1.4 [−2.3; −0.6]) muscles, but not the biceps muscle, during the measurements with exoskeleton than without, suggesting effectiveness of the exoskeleton. HR and discomfort did not statistically significantly differ between the two conditions. Participants would recommend an exoskeleton to their colleagues, but mainly for repetitive work. Their opinions about the usefulness during work varied.