Exoskeleton Research Articles

Development and characterization of sustainable concrete with marine shell waste

Resumo As atividades de mariscagem e malacocultura produzem uma grande quantidade de resíduos sólidos compostos por conchas marinhas. O impacto ambiental do descarte inadequado pode ser atenuado com estratégias de reaproveitamento. O objetivo deste trabalho é investigar a viabilidade do uso de resíduo de conchas marinhas com substituintes parciais de agregados no concreto. As características físicas do agregado reciclado foram investigadas através das técnicas de Microscopia de Força Atômica (MFA) e Microscopia Eletrônica de Varredura (MEV) a fim de esclarecer aspectos da superfície de contato com a pasta; as características químicas e mineralógicas foram investigadas por meio dos ensaios de fluorescência de raios-X e difração de raios-X; e o ensaio de resistência à compressão foi conduzido em amostras de concreto foram moldadas para avaliação do comportamento destes materiais do comportamento destes materiais como agregado (concha tipo A) e fíler (concha tipo B). Concluiu-se que o uso de até 20% de substituição de concha marinha como agregado graúdo e 10% como filer mostrou viabilidade para aplicações em concretos estruturais e, de forma complementar, teores de até 30% podem ser direcionados à concretos não estruturais.

Passive shoulder occupational exoskeleton reduces shoulder muscle coactivation in repetitive arm movements.

Humans naturally employ muscle coactivation to facilitate a broad range of movements, enhancing joint stability and movement accuracy. However, excessive muscle coactivation can become unfavorable or even detrimental. This phenomenon is often observed in industrial workers who endure repetitive or prolonged joint stress, particularly in areas such as the shoulders. Prolonged stress can result in soft tissue damage and the onset of work-related musculoskeletal disorders (MSDs). In recent years, there have been efforts to mitigate the emergence of work-related MSDs among industrial workers through the implementation of upper-limb occupational exoskeletons (OEs). While previous research has demonstrated their effectiveness in reducing shoulder muscle activation, particularly in static and overhead work activities, there has been a lack of studies examining the impact of upper-limb OEs on muscle coactivation during repetitive arm movements. To bridge this gap in knowledge, our study systematically assesses the influence of a passive exoskeleton's anti-gravitational support on shoulder muscle coactivation during repetitive arm movements. Results show that peak and mean coactivation levels linearly decrease with the increase of the amount of anti-gravitational support provided by the upper-limb OE, reaching approximately 51% and 54%, respectively. Conversely, the percentage of the movement cycle corresponding to the coactivation peak appears unaffected by the level of assistance. This study marks the first instance in which a passive upper-limb OE has been shown to reduce shoulder muscle coactivations, potentially paving the way for a novel methodology in their evaluation.

High-Performance Concrete from Rubber and Shell Waste Materials: Experimental and Computational Analysis

Waste and its environmental impact have driven the search for sustainable solutions across various industries, including construction. This study explores the incorporation of solid waste in the production of eco-friendly structural concrete, aiming to reduce pollution and promote ecological and sustainable construction practices. In this context, two types of eco-friendly concrete were produced using marine shells and recycled rubber as waste materials and compared with conventional concrete through experimental and computational approaches. The results demonstrated that the concrete with marine shells achieved a compressive strength of 32.4 MPa, 26.5% higher than conventional concrete, and a 1% reduction in weight. In contrast, the recycled rubber concrete exhibited a compressive strength of 22.5 MPa, with a 2 MPa decrease compared to conventional concrete, but a 4.3% reduction in density. Computational analysis revealed that porosity affects Young’s modulus, directly resulting in a reduction in the maximum achievable strength. This work demonstrates that it is feasible to produce eco-friendly structural concrete through the proper integration of industrial waste, contributing to decarbonization and waste valorization.

Scalable O(log2n) Dynamics Control for Soft Exoskeletons

Robotic exoskeletons are being actively applied to support the activities of daily living (ADL) for patients with hand motion impairments. In terms of actuation, soft materials and sensors have opened new alternatives to conventional rigid body structures. In this arena, biomimetic soft systems play an important role in modeling and controlling human hand kinematics without the restrictions of rigid mechanical joints while having an entirely deformable body with limitless points of actuation. In this paper, we address the computational limitations of modeling large-scale articulated systems for soft robotic exoskeletons by integrating a parallel algorithm to compute the exoskeleton’s dynamics equations of motion (EoM), achieving a computation with O(log2n) complexity for the highly articulated n degrees of freedom (DoF) running on p processing cores. The proposed parallel algorithm achieves an exponential speedup for n=p=64 DoF while achieving a 0.96 degree of parallelism for n=p=256, which demonstrates the required scalability for controlling highly articulated soft exoskeletons in real time. However, scalability will be bounded by the n=p fraction.

Progress and development trends of lower limb exoskeleton rehabilitation robots

Abstract. Currently, as the aging population intensifies, many elderly people are trapped by lower limb dysfunctions caused by diseases such as stroke sequelae, spinal cord injuries, and bone injuries. Research on lower limb exoskeleton robots has made progress both domestically and internationally. Foreign lower limb exoskeleton robot technology is very mature and widely applied; although starting later, domestic development in this field has been rapid. This paper studies the key technologies of lower limb exoskeleton robots from several aspects: the degrees of freedom in human lower limb movement, the cyclic movement of human gait, structural design, driving methods, and interactive control. With the continuous advancement of technology, lower limb exoskeleton robots will become more intelligent and focus more on personalized services and wearing comfort in future development, aiming to bring more convenience and help to disabled individuals, rehabilitation patients, and groups with special needs.

Deep Learning-Driven Analysis of a Six-Bar Mechanism for Personalized Gait Rehabilitation

Abstract Recent advances in robotics and artificial intelligence have highlighted the potential for the integration of computational intelligence in enhancing the functionality and adaptability of robotic systems, particularly in rehabilitation. Designing robotic exoskeletons for the lower limb rehabilitation of post-stroke patients requires frequent adjustments to accommodate individual differences in leg anatomy. This complex engineering challenge necessitates a deep understanding of human physiology, robotics, and optimization to develop adaptive robotic systems and also to swiftly quantify the required adjustments and implement them for each patient. The conventional approaches, which mostly rely on heuristics and manual tuning, often struggle to achieve optimal results. This paper presents a novel method that integrates a genetic algorithm with a deep learning approach to generate a gait trajectory of the ankle joint from a six-bar linkage mechanism of fixed dimensions. Later, using the same approach, the inverse kinematics solution for this mechanism is also devised whereby, the set of the link dimensions of the six-bar linkage mechanism is obtained for the given gait trajectory of an individual to achieve customization. We simulated the kinematic behavior of the six-bar linkage mechanism within defined mechanical constraints and utilized the generated data for training a feedforward neural network and long short-term memory models. The proposed model, when trained, can produce accurate lengths for the desired gait trajectories in the sagittal plane and vice versa, which further validates our proposed approach for inverse kinematics solution. Moreover, to evaluate the efficiency of deep learning models, we have conducted an extensive error-based, comparative, and sensitivity analysis using different performance indices. The results highlight the potential of the proposed deep-learning-driven approach in the design analysis of gait rehabilitation robots.

A wearable hip exoskeleton for anaerobic exercise in healthy adults

Guidelines encouraging social distancing, limited outings, and remote work due to COVID-19 have increased sedentary periods and reduced levels of physical activity. These habits increase the risk of metabolic diseases, obesity, cardiovascular disease, and diabetes mellitus. The World Health Organization recommends muscle-strengthening exercises as well as regular physical activity to promote overall health. This study investigates the effect of a wearable hip exoskeleton on muscle activity and heart rate during anaerobic exercise in 40 healthy adults (mean age of 40.00 ± 11.51 years; n = 20 females). Bot Fit, a wearable hip-type robotic exoskeleton, was developed by Samsung Electronics Co., Ltd. (Suwon, Republic of Korea) to enhance the effects of both aerobic and anaerobic exercise. All study participants performed a fitness exercise protocol, including knee-ups, good mornings, squats, mountain climbs, kick-backs, reverse lunges, and split jacks, with and without a Bot Fit. To evaluate the effect of anaerobic exercise with the Bot Fit, muscle activity and heart rate were measured during fitness exercises with and without a Bot Fit. Measured muscles were the rectus abdominis (RA), erector spinae (ES), rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), tibialis anterior (TA), gastrocnemius medialis (GCM), and gluteus maximus (GM). During anaerobic exercises with the Bot Fit, there was a significant increase in muscle activity compared to exercising without the Bot Fit. Muscle activity increased significantly in the RA, RF, VL, BF and TA muscles during knee-ups; in the ES, BF, and GM during good mornings; in the RF, VL, VM, BF, and GM during squats; in RA, RF, VL, VM, and GM during mountain climbs; in the RA and BF during kick-backs; in the RF, BF, and GCM during reverse lunges; and in the RF and VL during split jacks (p < 0.05). Heart rates showed a statistically significant increase during good mornings, mountain climbs, and reverse lunge exercises while wearing the Bot Fit (p < 0.05). This study demonstrated that anaerobic exercises by healthy adults using a Bot Fit led to enhanced activation of abdominal and lower-limb muscles as well as an improved heart rate, maximizing the effect of anaerobic exercise compared with the same exercise protocol without a Bot Fit. This suggests that use of a Bot Fit can increase the effectiveness of anaerobic exercise in healthy adults.

Ankle Moment Estimation Based on A Novel Distributed Plantar Pressure Sensing System.

Ankle moment plays an important role in human gait analysis, patients' rehabilitation process monitoring, and the human-machine interaction control of exoskeleton robots. However, current ankle moment estimation methods mainly rely on inverse dynamics (ID) based on optical motion capture system (OMC) and force plate. These methods rely on fixed instruments in the laboratory, which are difficult to be applied to the control of exoskeleton robots. To solve this problem, this paper developed a new distributed plantar pressure system and proposed an ankle plantar flexion moment estimation method using the plantar pressure system. We integrated eight pressure sensors in each insole to collect the pressure data of the key area of the foot and then used the plantar pressure data to train four neural networks to obtain the ankle moment. The performance of the models was evaluated using normalized root mean square error (NRMSE) and cross-correlation coefficient (ρ). During experiments, eight subjects were recruited for the overground walking tests, and OMC and force plate were used as the gold standard. The results indicate that the Genetic algorithm - Gated recurrent unit estimation algorithm (GA-GRU) was the best estimation model which achieved the highest accuracy in generalized ankle moment estimation (NRMSE = 7.23%, ρ = 0.85) compared with the other models. The designed novel distributed plantar pressure system and the proposed method could serve as a joint moment estimation approach in wearable robot control and human motion state monitoring.

Safety in Wearable Robotic Exoskeletons: Design, Control, and Testing Guidelines

Abstract Exoskeletons, wearable robotic devices designed to enhance human strength and endurance, find applications in various fields such as healthcare and industry; however, stringent safety measures should be adopted in such settings. This paper presents a comprehensive exploration of challenges associated with exoskeleton technology, ranging from mechanical issues to regulatory and ethical considerations. The enumerated challenges include joint hyper-extension or flexion, rapid or sudden motion, misalignment, fit, and comfort issues, mechanical failure, weight and mobility limitations, environmental challenges, power supply issues, high energy consumption and regeneration, fall risk or stability concerns, sensor failures, control algorithm malfunctions, machine-learning model challenges, communication disconnection, actuator malfunctions, unexpected human–robot interactions, and regulatory and ethical considerations. The paper outlines possible risks and suggests practical solutions based on design, control, and testing methods for each challenge. The objective is to offer a guideline for developers and users, emphasizing safety, reliability, and optimal performance in the ever-evolving landscape of exoskeleton technology. The guideline covers preoperation checks, user training, emergency response, real-time monitoring, and user interaction to ensure responsible innovation and user-centricity in exoskeleton development and deployment.

Possibilities of exoskeletal rehabilitation of post-traumatic brachial plexopathy

Post-traumatic brachial plexopathy (PTPP) in 70% of cases is a consequence of a road traffic accident, the remaining cases are due to sports, industrial, domestic injuries, as well as shrapnel and mine-explosive wounds received during military operations. Even successful microsurgical reconstruction followed by medical therapy and rehabilitation does not guarantee complete recovery, which prompts the search for new ways to restore patients with PTPP. This work demonstrates the capabilities of a domestic development - the passive exoskeleton of the upper limb "EXAR-34".

A lightweight semi-active ankle exoskeleton utilized NiTiCu-based shape memory alloys for energy storage.

Nowadays, exoskeletons have a place in many fields, such as industrial production, medical rehabilitation, and military. However, there are still many shortcomings in the existing exoskeleton, such as heavyweight and complex structures for active exoskeleton. The driving ability of passive exoskeletons is limited. To reduce the energy consumption of wearers, based on the characteristics of the semi-active ankle exoskeleton, this paper proposes to use NiTiCu-based shape memory alloys (SMA) as the energy storage source to improve the power density. Compared to NiTi-based SMA, the phase transformation process of NiTiCu-based SMA is more rapid, which can solve the response delay problem to a certain extent. The ankle exoskeleton uses SMA deformation to compress the bias spring. When the human ankle joint needs auxiliary torque, the SMA releases the energy stored by the bias spring and transfers the energy to the ankle exoskeleton to achieve the effect of assisting the human ankle joint. During the assistance process, a control system based on the SMA mathematical model is constructed. The above-mentioned ideas provide a new approach for further expanding power density and can be widely applied in the field of robotics. During characterization, this semi-active ankle exoskeleton can effectively complete the movement state of upstairs and walking, achieve an effective power of 180 N, and store maximum energy up to 5J for the human ankle.

Evaluation of All-Atom and Martini 3 Coarse-Grained Force Fields from the Structural Investigation of Nitroxide Spin Probes and Their Confinement in Beta-Cyclodextrin.

Nitroxide radicals have found wide applications as spin labels or probes, and their guest-host interactions with cyclodextrins exhibit enhanced applications in electron spin resonance (ESR) spectroscopy and imaging due to improved biostability toward reducing agents. Although the computational prediction of the guest-host binding has become increasingly common for small ligands, molecular simulations regarding the conformational preferences of hosted spin probes have not been conducted. Here we present molecular dynamics simulations at an atomistic level for a set of four TEMPO (2,2,6,6-tetramethylpiperidine 1-oxyl) spin probes and thereafter develop coarse-grained models compatible with the recent version of the Martini force field (v 3.0) to tackle their encapsulation in the cavity of β-cyclodextrin (βCD) for which experimental ESR data are available. The results indicate that the atomistic descriptions perform well in relation to the structural parameters derived from X-ray diffraction as well as hydrogen bonding and hydrogen patterns and predict that the guest-host complexation is hydrophobically driven by the presence of a methyl group pair of the spin probe at the cavity center of βCD. The spin probe mobility at the binding site reveals the nitroxide group orientation toward the secondary rim of the cyclodextrin and the alternating presence of the two methyl group pairs inside the cavity, features in agreement with the experimental behavior of the ESR parameters. The coarse-grained parameterizations of TEMPO probes and βCD rely on optimizing the bonded and nonbonded parameters with references to the atomistic simulation results, and they are capable of recovering the orientation and location of the spin probe inside the cyclodextrin cavity predicted by the atomistic guest-host complexes. The results suggest the cyclodextrin host-guest system as a powerful validation suite to evaluate new coarse-grained parameterizations of small ligands and future extensions to functionalized cyclodextrins in inclusion complexes.

Gravity support from a robotic exoskeleton increases spontaneous use of the non-dominant upper extremity during a choice reaching task.

The objective was to determine if gravity support for the left arm of right-handed participants would increase left arm use during a 3D reaching task in virtual reality. Twelve healthy control participants each completed 630 reaching movements broken into 6 blocks. The majority of targets were placed close to the mid-sagittal plane at three heights and participants were free to use either limb when reaching for targets. The hand had to stay in the target for a prescribed dwell time before the target disappeared. For all reaching tasks within a block, the left arm gravity support was set to either 0% or 75% of full arm support. The blocks also varied in the dwell time (2, 4, or 6 sec). The order of blocks was balanced across participants in terms of gravity support level and dwell time. EMG level in the left medial deltoid decreased with increasing gravity support (p<.001) and was higher for higher targets compared to lower targets (p<.001). The odds of using the left arm were 1.95 times higher with gravity support compared to no support (p<.001). With gravity support, we expected greater shifts towards the left arm in tasks that were more energetically demanding. This was not the case, as the increased use was evenly distributed across all target heights, and use decreased or remained unchanged with increasing dwell time. Results are discussed relative to current models of limb choice and the potential use of robotic gravity support to overcome learned non-use in stroke patients.

Experience of using the passive exoskeleton EXAR-34 in complex rehabilitation of a patient with post-traumatic plexopathy due to gunshot cervicothoracic wound (clinical observation)

The use of passive exoskeletons is a promising direction in the treatment of patients with severe combat injuries to the shoulder girdle, leading to disability in 30 % of cases. Aim: To demonstrate the capabilities of the passive exoskeleton EXAR-34 in the rehabilitation and habilitation of a victim with damage to the branches of the brachial nerve plexus. Materials and methods: An analysis of medical documentation, physical examination, morphometry, and goniometry were carried out. Clinical observation and discussion: A patient with post-traumatic left-sided plexopathy due to a gunshot perforating shrapnel cervicothoracic wound with gunshot fractures of the transverse processes of C6, C7, Th3 vertebrae, I–III ribs on the left after reconstructive intervention on elements of the brachial nerve plexus, when previously carried out rehabilitation measures were ineffective, during the first fitting of the EXAR-34 device, the range of active movements in the joints of the injured limb increased to 37,1–60,7 %, and routine motor skills were restored. Conclusion:The experience of using the EXAR-34 device demonstrates high promise in complex rehabilitation and habilitation of patients after reconstructive interventions on the brachial plexus for combat wounds.

Upper limb exoskeleton rehabilitation robot inverse kinematics modeling and solution method based on multi-objective optimization

The inverse kinematics problem of exoskeleton rehabilitation robots is challenging due to the lack of a standard analytical model, resulting in a complex and varied solution process. This complexity is especially pronounced in redundant upper limb exoskeleton robots, where inefficient solutions hinder the robot’s ability to adapt to the kinematic shape of the upper limb. This paper proposes a modeling and solution method based on multi-objective optimization to address the inverse kinematics of upper limb exoskeleton robots. We analyzed and validated this method using a redundant upper limb exoskeleton rehabilitation robot system developed by ourselves. First, we established a multi-objective inverse kinematics solution model by defining the end-position function, joint motion comfort function, system energy consumption function, motion safety, and human-like constraints. Then, the solution was designed based on the Improved Equilibrium Optimization (IEO) algorithm and validated its computational performance in terms of optimization ability, accuracy, and robustness. Finally, we experimentally tested the inverse kinematics solution model with the IEO algorithm on discrete objectives and continuous training trajectories using a redundant upper limb exoskeleton rehabilitation robot system. The results show that by incorporating the joint comfort function, system energy consumption function, and human-like constraints into the inverse kinematics model, we can not only quickly solve the inverse kinematics of redundant upper limb exoskeleton robots but also significantly improve the robot’s motion shape. Furthermore, it has better solution accuracy and stronger robustness than other algorithms when solving this inverse kinematics model based on the IEO algorithm.

Structure design and ergonomic assessment of a passive exoskeleton supporting the lead apron for interventional surgery

Structure design and ergonomic assessment of a passive exoskeleton supporting the lead apron for interventional surgery

Lower Limb Rehabilitation Exoskeleton Robots, A review

Using a lower limb exoskeleton for rehabilitation (LLE) Lower limb exoskeleton rehabilitation robots (LER) are designed to assist patients with daily duties and help them regain their ability to walk. Even though a substantial portion of them is capable of doing both, they have not yet succeeded in conducting agile and intelligent joint movement between humans and machines, which is their ultimate goal. The typical LLE products, rapid prototyping, and cutting-edge techniques are covered in this review. Restoring a patient's athletic prowess to its pr-accident level is the aim of rehabilitation treatment. The core of research on lower limb exoskeleton rehabilitation robots is the understanding of human gait. The performance of common prototypes might be used to match wearable robot shapes to human limbs. To imitate a normal stride, robot-assisted treatment needs to be able to control the movement of the robot at each joint and move the patient's limb.

Dosing overground robotic gait training after spinal cord injury: a randomized clinical trial protocol

BackgroundRobotic exoskeletons have changed rehabilitation care available to people after spinal cord injury (SCI). Yet, the current evidence base is insufficient to identify the optimal dose and neurophysiological mechanism of robotic exoskeleton gait training (RGT) as an effective rehabilitation approach. This study will (1) examine whether the frequency of RGT after motor incomplete SCI impacts function and health outcomes, (2) analyze the neuroplastic effects of RGT dose, and (3) evaluate the safety, tolerability, and feasibility of delivering RGT.MethodsWe will enroll 144 participants with motor incomplete SCI admitted to inpatient rehabilitation within 6 months of SCI. Participants will be randomized based on injury severity and level into one of 3 RGT frequency groups (high, moderate, low) or none/usual care only. Participants will complete 24 RGT sessions and be assessed at admission and discharge to inpatient rehabilitation, post-RGT intervention, 1-month post-RGT, and 9-month post-SCI. Outcomes include Walking Index for Spinal Cord Injury-II, health outcomes (gait speed, Spinal Cord Independence Measure, pain, fatigue, spasticity, general health, quality of life, physical activity), and motor evoked potential amplitudes obtained using transcranial magnetic stimulation.DiscussionSuccessful completion of this study will provide an evidence-based intervention, specifically tailored to meet the unique needs of people with SCI, which supports walking recovery; maximizing health, function, and ultimately participation. The intervention will further support widespread clinical implementation of exoskeleton use during acute rehabilitation.Trial registrationClinicalTrials.gov NCT05218447. Registered on June 23, 2022.

Mobility Assistive Technology (AT) for Children with Cerebral Palsy (CP): A Literature Review

This paper comprehensively reviews the use of mobility Assistive Technology (MAT) in children with Cerebral Palsy (CP). Currently, 9 million people are severely affected by CP, the most serious form of movement disability, characterized by deficits in movement, posture, and more, alongside cognitive and sensory deficits. These impairments restrict the child’s functionality in self-care, performing tasks associated with daily living, and socialization. The main purpose of this paper is to establish the role of MAT in supporting children with CP and assess its impact on their lives. This review describes a range of devices that enhance mobility in motor-disabled patients such as powered wheelchairs, robotic exoskeletons, ankle-foot orthoses (AFO), and gait trainers, and examines their effects on the psychosocial well-being and physical growth of children with CP. A methodical search performed within the PRISMA framework enabled us to analyze papers from 2010 to 2024, discussing the advantages and disadvantages of assistive technology (AT). It was noted that although ATs can improve independence, social involvement, and mobility, challenges remain such as high costs, poor design, and unavailability of these resources in underprivileged regions. New information technologies, including intelligent systems and virtual reality (VR) training tools, are effective in addressing health-related issues; however, the optimization of these techniques over a long period needs further study. This paper underscores the importance of a more child-centred design of AT devices and additional policy adjustments to enhance accessibility across different socio-economic strata. Through this review, we seek to advance the emerging understanding of the role of mobility AT in enhancing the lives of children with CP, focusing on identifying weaknesses in the existing research and suggesting possible advancements.

Kinematic-Muscular Synergies Describe Human Locomotion with a Set of Functional Synergies.

Kinematics, kinetics and biomechanics of human gait are widely investigated fields of research. The biomechanics of locomotion have been described as characterizing muscle activations and synergistic control, i.e., spatial and temporal patterns of coordinated muscle groups and joints. Both kinematic synergies and muscle synergies have been extracted from locomotion data, showing that in healthy people four-five synergies underlie human locomotion; such synergies are, in general, robust across subjects and might be altered by pathological gait, depending on the severity of the impairment. In this work, for the first time, we apply the mixed matrix factorization algorithm to the locomotion data of 15 healthy participants to extract hybrid kinematic-muscle synergies and show that they allow us to directly link task space variables (i.e., kinematics) to the neural structure of muscle synergies. We show that kinematic-muscle synergies can describe the biomechanics of motion to a better extent than muscle synergies or kinematic synergies alone. Moreover, this study shows that at a functional level, modular control of the lower limb during locomotion is based on an increased number of functional synergies with respect to standard muscle synergies and accounts for different biomechanical roles that each synergy may have within the movement. Kinematic-muscular synergies may have impact in future work for a deeper understanding of modular control and neuro-motor recovery in the medical and rehabilitation fields, as they associate neural and task space variables in the same factorization. Applications include the evaluation of post-stroke, Parkinson's disease and cerebral palsy patients, and for the design and development of robotic devices and exoskeletons during walking.