Passive Exoskeletons During Live Surgeries: Supporting Forward Head Postures Among Veterinary Surgeons.

TECHNICAL ABSTRACTBackground: Musculoskeletal symptoms (MSS) are prevalent among veterinary surgeons. Recent research has proposed exoskeletons as potential solutions in reducing the risk of musculoskeletal disorders among surgeons, but no studies have addressed the neck forward postures (opposite of overhead work), a unique ergonomic neck risk, commonly required during live, open surgery. Purpose: We explored the effectiveness of a passive neck-support exoskeleton during live veterinary surgical procedures with experienced surgeons. Methods: We employed a within-subject crossover design involving surgeons who participated in procedures across specialties including soft tissue and orthopedics. Participants performed entire surgeries with and without a front head posture support prototype exoskeleton, and they completed pre- and post-surgical surveys to assess MSS and perceived effort. The Wilcoxon Signed Rank Test was used to compare median values of MSS and the perceived effort of each participant when they operated with and without the exoskeleton. Results: We collected data during 28 procedures involving eight surgeons, with each subject performing at least one surgery with (intervention) and at least one surgery without (control) the exoskeleton (randomized order). The number of control and intervention cases for each participant was balanced. We found that the difference in neck stiffness before and after surgery was greater in the control surgeries compared to when using the exoskeleton intervention. Increases in neck pain and neck stiffness were only observed in control cases, whereas no participant reported increased neck pain or neck stiffness when the exoskeleton was used. Conclusion: Our results indicate that a passive forward head posture support exoskeleton is a promising intervention for reducing the risk of MSS in live surgical procedures.

Surgeons, including veterinary surgeons, are exposed to many ergonomic challenges due to their work settings. The prolonged, sustained neck flexion necessary during surgeries can lead to muscle fatigue and discomfort, potentially causing musculoskeletal disorders. Our research explored the use of a passive exoskeleton to provide support for forward head posture (FHP) during live veterinary surgeries in the field. Our findings indicate that the passive FHP support exoskeleton can potentially reduce musculoskeletal symptoms among surgeons. Further studies, though, are needed to continue generating biomechanical evidence to objectively assess the effectiveness of the exoskeleton in prolonged use.

Shoulder-assist exoskeleton effects on balance and muscle activity during a block-laying task on a simulated mast climber.

Interest in utilizing exoskeletons to mitigate the risks of musculoskeletal disorders (MSDs) among construction workers is growing, spurred by encouraging results in other industries. However, it is crucial to carefully examine their impact on workers' stability and balance before implementation. In this study, seven male participants lifted a 35-lb cinder block from a production table to a simulated wall at two heights-elbow and shoulder levels-using three different exoskeleton models on an unstable platform, where their balance and shoulder muscle activity were assessed. Balance-related parameters, included mean distance (MDIST), total excursion (EXCUR), and mean velocity (VEL) of the center of pressure, were derived from force plate data. Muscle activity in six shoulder and upper arm muscles was estimated using electromyography (EMG) data. The results indicated that wearing two of the exoskeletons significantly increased both total and medio-lateral (ML) MDIST compared to not wearing an exoskeleton. Wearing one of the exoskeletons significantly increased total and ML VEL and ML EXCUR. Although lifting level did not have a significant impact on the balance parameters, it did affect the muscle activity in most of the measured muscles. Moreover, only one exoskeleton significantly reduced the activity in a particular shoulder muscle compared to no exoskeleton use. In conclusion, the evaluated shoulder-assist exoskeletons showed limited benefits for preventing upper extremity MSDs and may negatively affect whole-body balance during a block-laying task on an unstable platform. These findings underscore the importance of comprehensive evaluations of balance and effectiveness prior to adopting exoskeletons in construction.

Effects of a back-assist exosuit in lab-based approximations of construction tasks performed by novices and experienced construction workers.

Passive back-assist exosuits may be beneficial for construction workers, but few evaluations have been conducted with actual workers and construction-relevant tasks. This paper presents a laboratory study of the HeroWear Apex exosuit with 35 participants: 15 with significant construction experience and 20 without it. Participants completed several approximations of brief construction tasks (lifting, carrying, raising boards) and three 3-min tasks (hunched standing, kneeling, hunched walking with a nail gun) with and without the exosuit. During brief tasks, erector spinae electromyograms were reduced in all tasks (Cohen's d up to -0.58), kinematics suggested load shifting from the back to the legs, and the exosuit was perceived as helpful. During 3-min tasks, the exosuit was perceived as helpful in all tasks, but only reduced erector spinae electromyograms during kneeling. Thus, the exosuit may benefit workers during several construction-related tasks, though objective benefits could not be shown in 3-min standing or walking.

This study explored how a passive back-assist exosuit affects back muscle activity and kinematics in lab-based approximations of construction tasks performed by both novices and experienced construction workers. Quantitative and qualitative results indicated potential benefits in several brief load lifting and carrying tasks, but not during 3-min standing or walking.

Active back exosuits demonstrate positive usability perceptions that drive intention-to-use in the field among logistic warehouse workers.

Back exosuits offer the potential to reduce occupational back injuries but require in-field acceptance and use to realize this potential. For this study, 146 employees trialed an active back exosuit in the field for 4 h, completing an acceptance usability survey. Comparing the 80% of employees willing to continue wearing this device (N = 117) to those who were not (N = 29) revealed that employees willing to wear this device for a longer-term study generally were more likely to perceive this back exosuit to be effective (helpful) and compatible (minimally disruptive) to their everyday work. Using an optimal tree approach, we demonstrate that intent-to-use could be predicted with 78% accuracy by interacting features of perceived exosuit effectiveness and work compatibility. This study reinforces the importance of task matching, noticeable relief, and unobtrusive design to facilitate short-term employee acceptance of industrial wearable robotic technology.

A new modular neuroprosthesis suitable for hybrid FES-robot applications and tailored assistance.

BACKGROUND: To overcome the application limitations of functional electrical stimulation (FES), such as fatigue or nonlinear muscle response, the combination of neuroprosthetic systems with robotic devices has been evaluated, resulting in hybrid systems that have promising potential. However, current technology shows a lack of flexibility to adapt to the needs of any application, context or individual. The main objective of this study is the development of a new modular neuroprosthetic system suitable for hybrid FES-robot applications to meet these needs. METHODS: In this study, we conducted an analysis of the requirements for developing hybrid FES-robot systems and reviewed existing literature on similar systems. Building upon these insights, we developed a novel modular neuroprosthetic system tailored for hybrid applications. The system was specifically adapted for gait assistance, and a technological personalization process based on clinical criteria was devised. This process was used to generate different system configurations adjusted to four individuals with spinal cord injury or stroke. The effect of each system configuration on gait kinematic metrics was analyzed by using repeated measures ANOVA or Friedman's test. RESULTS: A modular NP system has been developed that is distinguished by its flexibility, scalability and personalization capabilities. With excellent connection characteristics, it can be effectively integrated with robotic devices. Its 3D design facilitates fitting both as a stand-alone system and in combination with other robotic devices. In addition, it meets rigorous requirements for safe use by incorporating appropriate safety protocols, and features appropriate battery autonomy, weight and dimensions. Different technological configurations adapted to the needs of each patient were obtained, which demonstrated an impact on the kinematic gait pattern comparable to that of other devices reported in the literature. CONCLUSIONS: The system met the identified technical requirements, showcasing advancements compared to systems reported in the literature. In addition, it demonstrated its versatility and capacity to be combined with robotic devices forming hybrids, adapting well to the gait application. Moreover, the personalization procedure proved to be useful in obtaining various system configurations tailored to the diverse needs of individuals.

Effects of using an active hand exoskeleton for drilling tasks: A pilot study.

INTRODUCTION: Several studies have assessed and validated the impact of exoskeletons on back and shoulder muscle activation; however, limited research has explored the role that exoskeletons could play in mitigating lower arm-related disorders. This study assessed the impact of Ironhand, an active hand exoskeleton (H-EXO) designed to reduce grip force exertion, on worker exertion levels using a two-phase experimental design. METHOD: Ten male participants performed a controlled, simulated drilling activity, while three male participants completed an uncontrolled concrete demolition activity. The impact of the exoskeleton was assessed in terms of muscle activity across three different muscles using electromyography (EMG), perceived exertion, and perceived effectiveness. RESULTS: Results indicate that peak muscle activation decreased across the target muscle group when the H-EXO was used, with the greatest reduction (27%) observed in the Extensor Carpi Radialis (ECR). Using the exoskeleton in controlled conditions did not significantly influence perceived exertion levels. Users indicated that the H-EXO was a valuable technology and expressed willingness to use it for future tasks. PRACTICAL APPLICATIONS: This study showcases how glove-based exoskeletons can potentially reduce wrist-related disorders, thereby improving safety and productivity among workers. Future work should assess the impact of the H-EXO in various tasks, different work environments and configurations, and among diverse user groups.

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.

Improving Task-Agnostic Energy Shaping Control of Powered Exoskeletons with Task/Gait Classification.

Emerging task-agnostic control methods offer a promising avenue for versatile assistance in powered exoskeletons without explicit task detection, but typically come with a performance trade-off for specific tasks and/or users. One such approach employs data-driven optimization of an energy shaping controller to provide naturalistic assistance across essential daily tasks with passivity/stability guarantees. This study introduces a novel control method that merges energy shaping with a machine learning-based classifier to deliver optimal support accommodating diverse individual tasks and users. The classifier detects transitions between multiple tasks and gait patterns in order to employ a more optimal, task-agnostic controller based on the weighted sum of multiple optimized energy-shaping controllers. To demonstrate the efficacy of this integrated control strategy, an in-silico assessment is conducted over a range of gait patterns and tasks, including incline walking, stairs ascent/descent, and stand-to-sit transitions. The proposed method surpasses benchmark approaches in 5-fold cross-validation ( p < 0.05 ), yielding 93.17 ± 7.39% cosine similarity and 77.92 ± 19.76% variance-accounted-for across tasks and users. These findings highlight the control approach's adaptability in aligning with human joint moments across various tasks.

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.

Virtual muscles and reflex control generates human-like ankle torques during gait perturbations.

A biologically-inspired actuation system, including muscles, spinal reflexes, and vestibular feedback, may be capable of achieving more natural gait mechanics in powered prostheses or exoskeletons. In this study, we developed a Virtual Muscle Reflex (VMR) system to control ankle torque and tuned it using data from human responses to anteroposterior mechanical perturbations at three walking speeds. The system consists of three Hill-Type muscles, simulated in real time, and uses feedback from ground reaction force and from stretch sensors on the virtual muscle fibers. Controller gains, muscle properties, and reflex/vestibular time delays were optimized using Covariance Matrix Adaptation (CMA) to minimize the difference between the VMR torque output and the torque measured from the experiment. We repeated the procedure using a conventional finite-state impedance controller. For both controllers, the coefficient of determination (R2) and root-mean-square error (RMSE) was calculated as a function of time within the gait cycle. The VMR had lower RMSE than the impedance controller in 70%, and in 60% of the trials, the R2 of the VMR controller was higher than for the impedance controller. We concluded that the VMR system can better reproduce the human responses to perturbations than the impedance controller.

Ankle Exoskeletons May Hinder Standing Balance in Simple Models of Older and Younger Adults.

Humans rely on ankle torque to maintain standing balance, particularly in the presence of small to moderate perturbations. Reductions in maximum torque (MT) production and maximum rate of torque development (MRTD) occur at the ankle with age, diminishing stability. Ankle exoskeletons are powered orthotic devices that may assist older adults by compensating for reduced torque and power production capabilities. They may also be able to assist with ankle strategies used for balance. However, the effect of such devices on standing balance in older adults is not well understood. Here, we model the effects ankle exoskeletons have on stability in physics-based models of healthy young and old adults, focusing on the potential to mitigate age-related deficits in MT and MRTD. Using backward reachability, a mathematical technique for analyzing the behavior of dynamical systems, we compute the set of stable center of mass positions and velocities for sex and age adjusted models of human standing balance with an ankle exoskeleton. We show that an ankle exoskeleton moderately reduces feasible stability boundaries in users who have full ankle strength. For individuals with age-related deficits, there is a trade-off. While exoskeletons augment stability at low center of mass velocities, they reduce stability in some high velocity conditions. Our results suggest that well-established control strategies must still be experimentally validated in older adults.

Integrating musculoskeletal simulation and machine learning: a hybrid approach for personalized ankle-foot exoskeleton assistance strategies.

Introduction: Lower limb exoskeletons have shown considerable potential in assisting human walking, particularly by reducing metabolic cost (MC), leading to a surge of interest in this field in recent years. However, owing to significant individual differences and the uncertainty of movements, challenges still exist in the personalized design and control of exoskeletons in human-robot interactions. Methods: In this study, we propose a hybrid data-driven approach that integrates musculoskeletal simulation with machine learning technology to customize personalized assistance strategies efficiently and adaptively for ankle-foot exoskeletons. First, optimal assistance strategies that can theoretically minimize MC, were derived from forward muscle-driven simulations on an open-source dataset. Then, a neural network was utilized to explore the relationships among different individuals, movements, and optimal strategies, thus developing a predictive model. Results: With respect to transfer learning, our approach exhibited effectiveness and adaptability when faced with new individuals and movements. The simulation results further indicated that our approach successfully reduced the MC of calf muscles by approximately 20% compared to normal walking conditions. Discussion: This hybrid approach offers an alternative for personalizing assistance strategy that may further guide exoskeleton design.

Human-Exoskeleton Coupling Simulation for Lifting Tasks with Shoulder, Spine, and Knee-Joint Powered Exoskeletons.

In this study, we introduce a two-dimensional (2D) human skeletal model coupled with knee, spine, and shoulder exoskeletons. The primary purpose of this model is to predict the optimal lifting motion and provide torque support from the exoskeleton through the utilization of inverse dynamics optimization. The kinematics and dynamics of the human model are expressed using the Denavit-Hartenberg (DH) representation. The lifting optimization formulation integrates the electromechanical dynamics of the DC motors in the exoskeletons of the knee, spine, and shoulder. The design variables for this study include human joint angle profiles and exoskeleton motor current profiles. The optimization objective is to minimize the squared normalized human joint torques, subject to physical and task-specific lifting constraints. We solve this optimization problem using the gradient-based optimizer SNOPT. Our results include a comparison of predicted human joint angle profiles, joint torque profiles, and ground reaction force (GRF) profiles between lifting tasks with and without exoskeleton assistance. We also explore various combinations of exoskeletons for the knee, spine, and shoulder. By resolving the lifting optimization problems, we designed the optimal torques for the exoskeletons located at the knee, spine, and shoulder. It was found that the support from the exoskeletons substantially lowers the torque levels in human joints. Additionally, we conducted experiments only on the knee exoskeleton. Experimental data indicated that using the knee exoskeleton decreases the muscle activation peaks by 35.00%, 10.03%, 22.12%, 30.14%, 16.77%, and 25.71% for muscles of the erector spinae, latissimus dorsi, vastus medialis, vastus lateralis, rectus femoris, and biceps femoris, respectively.

An ethical assessment of powered exoskeletons: Implications from clinical use to industry and military contexts.

Exoskeletons are technologies that can help to increase or improve mobility, dexterity, and strength. They can be used as assistive devices, to restore lost affordances, or for rehabilitation. While mechanical exoskeletons are passive and rely on the body's power for movement, powered exoskeletons are active mechanical systems that can assist or enhance a user's capacity, including in strength and performance. They also offer scope to augment or enhance beyond simple medical support, with potential in the future for superhuman power and strength. While these technologies present promising clinical opportunities, including for those who want to regain walking capacity, they also bring ethical questions, such as about data privacy and accessibility. In addition, the physical features of the technology can prove mentally, physically, and financially demanding, and may be deployed in contexts where user choice and autonomy is constrained. In this article, we discuss these issues, and raise some pertinent ethical questions, not all of which can be easily answered. We touch upon medical and therapeutic uses, for industrial and workplace settings, and in military contexts specially, given these are contexts where such technology may be required or even imposed. We argue that reasonable optimism for such technologies needs to be tempered by sufficient ethical assessment to identify and address barriers to research, development, and use. As well as managing any impacts and expectations for the health and wellbeing of users, the potential impact on autonomy and the risk of coercion, we have to consider what kind of data may be recorded or used, and the risk that these technologies could exacerbate existing inequalities or harms.

Evaluation of a passive wearable arm ExoNET.

Wearable ExoNETs offer a novel, wearable solution to support and facilitate upper extremity gravity compensation in healthy, unimpaired individuals. In this study, we investigated the safety and feasibility of gravity compensating ExoNETs on 10 healthy, unimpaired individuals across a series of tasks, including activities of daily living and resistance exercises. The direct muscle activity and kinematic effects of gravity compensation were compared to a sham control and no device control. Mixed effects analysis revealed significant reductions in muscle activity at the biceps, triceps and medial deltoids with effect sizes of -3.6%, -4.5%, and -7.2% rmsMVC, respectively, during gravity support. There were no significant changes in movement kinematics as evidenced by minimal change in coverage metrics at the wrist. These findings reveal the potential for the ExoNET to serve as an alternative to existing bulky and encumbering devices in post-stroke rehabilitation settings and pave the way for future clinical trials.

Positional Analysis of Assisting Muscles for Handling-Assisted Exoskeletons.

In order to better design handling-assisted exoskeletons, it is necessary to analyze the biomechanics of human hand movements. In this study, Anybody Modeling System (AMS) simulation was used to analyze the movement state of muscles during human handling. Combined with surface electromyography (sEMG) experiments, specific analysis and verification were carried out to obtain the position of muscles that the human body needs to assist during handling. In this study, the simulation and experiment were carried out for the manual handling process. A treatment group and an experimental group were set up. This study found that the vastus medialis muscle, vastus lateralis muscle, latissimus dorsi muscle, trapezius muscle, deltoid muscle and triceps brachii muscle require more energy in the process of handling, and it is reasonable and effective to combine sEMG signals with the simulation of the musculoskeletal model to analyze the muscle condition of human movement.

Emerging Medical Technologies and Their Use in Bionic Repair and Human Augmentation.

As both the proportion of older people and the length of life increases globally, a rise in age-related degenerative diseases, disability, and prolonged dependency is projected. However, more sophisticated biomedical materials, as well as an improved understanding of human disease, is forecast to revolutionize the diagnosis and treatment of conditions ranging from osteoarthritis to Alzheimer's disease as well as impact disease prevention. Another, albeit quieter, revolution is also taking place within society: human augmentation. In this context, humans seek to improve themselves, metamorphosing through self-discipline or more recently, through use of emerging medical technologies, with the goal of transcending aging and mortality. In this review, and in the pursuit of improved medical care following aging, disease, disability, or injury, we first highlight cutting-edge and emerging materials-based neuroprosthetic technologies designed to restore limb or organ function. We highlight the potential for these technologies to be utilized to augment human performance beyond the range of natural performance. We discuss and explore the growing social movement of human augmentation and the idea that it is possible and desirable to use emerging technologies to push the boundaries of what it means to be a healthy human into the realm of superhuman performance and intelligence. This potential future capability is contrasted with limitations in the right-to-repair legislation, which may create challenges for patients. Now is the time for continued discussion of the ethical strategies for research, implementation, and long-term device sustainability or repair.

Field assessment of active BSE: Trends over test days of subjective indicators and self-reported fatigue for railway construction workers.

The research community has conducted several controlled "in -lab" assessments on the effectiveness of industrial exoskeletons, paving the way for their adoption. However, field testing, focusing on ergonomics and the user experience, could serve to enhance both end-users' awareness and address open doubts concerning true effectiveness of industrial exoskeletons. This study presents an analysis of qualitative data regarding the use of back-support exoskeletons during field trials in harsh civil engineering environments. This work evaluates the StreamEXO's (an active back-support exoskeleton) efficacy in reducing fatigue and the evolution of its perceived usefulness. This is achieved using qualitative data collection tools, during real scenarios testing over multiple-day trials. Collected data shows a positive correlation between self-reported fatigue, measured on a four verbal anchors-based Borg CR10 scale, and the use of the exoskeleton during physically demanding movements. Moreover, the evolution of scores throughout the testing sessions (90 minutes of exoskeleton use for three nonconsecutive days) suggests a trend due to the adaptation and learning curve of workers during the exoskeleton experience. The analysis of the open-ended answers highlights that the adaptation to physical interaction has a negative oscillation on day two to rise back during the third day, possibly correlated to a change in muscle pattern. The main critical factors affecting comfort during the exoskeleton experience are weight balance, body pressure, and thermal comfort, which can strongly affect device acceptance.

In-Field Training of a Passive Back Exoskeleton Changes the Biomechanics of Logistic Workers.

OCCUPATIONAL APPLICATIONSOccupational exoskeletons receive rising interest in industry as these devices diminish the biomechanical load during manual materials handling. Still, we have limited knowledge when it comes to in-field use. This gap often contributes to failure in the implementation of exoskeleton in industry. In this study, we investigated how a training protocol consisting of in-field use of a passive back exoskeleton affected the biomechanics of logistic workers. More specifically, we focused on how the variation of the muscular and kinematic patterns of the user was altered after exoskeleton training. We found that training had a positive effect on exoskeleton use, as a relative decrease of 6-9% in peak back muscle activity was observed post-training. Additionally, training decreased knee flexion by 6°-16°, indicating a more stoop lifting technique. The findings point at the potential benefits of applying a training approach when implementing a back-supporting exoskeleton in logistics.

Background: Occupational exoskeletons are an attractive solution to reduce the prevalence of attrition and work-related musculoskeletal disorders, such as low back pain, among manual workers. However, research has mostly focused on acute effects, while the effects of in-field use, and exoskeleton training are still to be addressed. Purpose: The aim of the present paper was to investigate how in-field use and exoskeleton training affected the biomechanics, acceptance, and comfort of logistic workers when using a passive back exoskeleton. Methods: Twenty workers were randomly distributed into control and intervention group. The tests consisted of standard lifting tasks with and without exoskeleton before and after a 5-week period. The intervention group underwent a 5-week progressive training protocol aiming at increasing the duration of use of the exoskeleton. The variation in muscle activity (surface electromyography) and full-body kinematics (IMU-based motion capture) were assessed during logistic work tasks. Additionally, acceptance, comfort, and perceived effort were collected. Compliance to the training protocol reached 74%. Results: Using the exoskeleton resulted in a 13­20% reduced variation in muscle activity of the back muscles across groups and lifting conditions including trunk extension. The changes in variation were driven by a decrease in peak muscle activity, which was further lowered by 6­9% after the 5-week training. Additionally, training induced decreased knee flexion indicating a more stoop lifting technique in the intervention group. Conclusions: The present results demonstrate that exoskeleton training optimized the human-exoskeleton interaction by deriving more effects of the exoskeleton ­ in this case by lowering the peak muscle activity of the user during manual materials handling. This underlines the importance of introducing training when implementing exoskeletons in industry. Additionally, the results indicate that a progressive implementation of back supporting exoskeletons in logistics can be beneficial in terms of lowering the biomechanical load during manual materials handling.

Human-in-the-Loop Optimization of Knee Exoskeleton Assistance for Minimizing User's Metabolic and Muscular Effort.

Lower limb exoskeletons have the potential to mitigate work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls adapt an exoskeleton's assistance in real time, to optimize the user-exoskeleton interaction. This study presents a HITL control for a knee exoskeleton using a CMA-ES algorithm to minimize the users' physical effort, a parameter innovatively evaluated using the interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user's metabolic cost within the HITL control through a machine-learning model. The regression model estimated the metabolic cost, in real time, with a root mean squared error of 0.66 W/kg and mean absolute percentage error of 26% (n = 5), making faster (10 s) and less noisy estimations than a respirometer (K5, Cosmed). The HITL reduced the user's metabolic cost by 7.3% and 5.9% compared to the zero-torque and no-device conditions, respectively, and reduced the interaction torque by 32.3% compared to a zero-torque control (n = 1). The developed HITL control surpassed a non-exoskeleton and zero-torque condition regarding the user's physical effort, even for a task such as slow walking. Furthermore, the user-specific control had a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential of HITL controls in assisted walking.