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Background: The body of literature regarding the use of an upper limb exoskeleton during authentic working conditions is sparse. Objective: The aim of this study was to evaluate the effectiveness of an upper limb exoskeleton in reducing muscle strain during authentic industrial construction work. Methods: Fifteen male participants, comprising of roofers, scaffolders, builders, bricklayers, and graders performing overhead work participated in the study. During work without (REF) and with exoskeleton (EXO), muscle activity from 8 muscles, heart rate (HR), metabolic equivalent (MET), and upper arm elevation angles were recorded. Results: When using the exoskeleton, a significant reduction of 20.2% in average muscle activity of 8 muscles was found. The largest effect focused on m. deltoideus, where 46.2 and 32.2% reduction occurred in medial and anterior parts of the muscle, respectively. HR and MET were unaffected. Upper arm elevation angles were similar between REF and EXO, indicating equal biomechanical loading. Conclusions: This study indicates that exoskeletons show great promise in reducing the potential for musculoskeletal strain during authentic overhead construction work. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study is to evaluate how gait kinematics and muscle activity during robot-assisted gait training are affected by different combinations of parameter settings and a number of instruction types, ranging from no instructions to goal-specific instructions. Design: Robots for gait therapy provide a haptic guidance, but too much guidance can limit the active participation. Therapists can stimulate this active participation either with instructions or by adapting device parameters. How these two factors interact is still unknown. In the present study, we test the interaction of three different parameter settings and four instruction types in a cross-sectional study with 20 children and adolescents without impairment. Gait kinematics and surface electromyography were measured to evaluate the immediate effects. Results: We found that only goal-specific instructions in combination with a low guidance led to a moderate but significant change in gait kinematics. The muscle activity was altered by all instructions, but the biggest effect was found for goal-specific instructions with a 2.5 times higher surface electromyography amplitude compared to no instruction. Conclusions: Goal-specific instructions are a key element of robot assisted gait therapy interventions and device parameter adjustments may be used to modulate their effects. Therapists should pay close attention to how they instruct patients. [ABSTRACT FROM AUTHOR]

Lower-limb exoskeletons (LLEs) can provide rehabilitation training and walking assistance for individuals with lower-limb dysfunction or those in need of functionality enhancement. Adapting and personalizing the LLEs is crucial for them to form an intelligent human–machine system (HMS). However, numerous LLEs lack thorough consideration of individual differences in motion planning, leading to subpar human performance. Prioritizing human physiological response is a critical objective of trajectory optimization for the HMS. This paper proposes a human-in-the-loop (HITL) motion planning method that utilizes surface electromyography signals as biofeedback for the HITL optimization. The proposed method combines offline trajectory optimization with HITL trajectory selection. Based on the derived hybrid dynamical model of the HMS, the offline trajectory is optimized using a direct collocation method, while HITL trajectory selection is based on Thompson sampling. The direct collocation method optimizes various gait trajectories and constructs a gait library according to the energy optimality law, taking into consideration dynamics and walking constraints. Subsequently, an optimal gait trajectory is selected for the wearer using Thompson sampling. The selected gait trajectory is then implemented on the LLE under a hybrid zero dynamics control strategy. Through the HITL optimization and control experiments, the effectiveness and superiority of the proposed method are verified. [ABSTRACT FROM AUTHOR]

• An active hand Exoskeleton (H-EXO) was assessed for a drilling task. • H-EXO reduced peak muscle activation in the forearm by up to 27% • H-EXO minimally affected perceived discomfort in controlled experiment. • H-EXO reduced perceived exertion up to 11% in uncontrolled observation. • Users indicated that H-EXO was a valuable intervention. 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. [ABSTRACT FROM AUTHOR]

The objective of this study was to explore the effectiveness of a passive back-support exosuit at reducing low back muscle fatigue during an 18-minute trunk posture maintenance task. On two separate days sixteen participants performed an 18-minute trunk posture profile that reflected trunk flexion postures observed during a challenging vascular surgery procedure. On one day they performed the procedure with the support of the exosuit, on the other day without. Test contractions were performed every three minutes to capture the time-dependent electromyographic activity of the bilateral erector spinae muscles. Time domain (amplitude) and frequency domain (median frequency) measures of erector spinae muscle fatigue were assessed. Results revealed that the exosuit significantly reduced the measures of erector spinae muscle fatigue in terms of both amplitude (6.1%) and median frequency (5.3%), demonstrating a fatigue reduction benefit of the exosuit in a realistic surgical posture maintenance task. PRACTITIONER SUMMARY: To examine the potential adoption of a back-support exosuit system in the surgical environment, this study used an 18-minute posture maintenance task that reflected trunk flexion postures observed during a vascular surgery procedure and suggests that the exosuit system can effectively reduce low back muscle fatigue during a vascular surgical procedure. [ABSTRACT FROM AUTHOR]

This study evaluated the effects of a back-support exoskeleton on the trunk and hip joint angles, lower back muscle activity and heart rate during four patient handling tasks: assisting a patient from sitting to lying, laterally repositioning the patient and turning the patient in two directions. Eight participants performed these tasks with and without the exoskeleton. Results demonstrated a significant reduction in the lower back muscle activity, but less pronounced effects for other tasks involving minimal trunk flexion. Hip flexion angles were reduced for all tasks when the exoskeleton was worn. The amount of reduction in the muscle activity and changes in the trunk and hip angles varied by task. The exoskeleton did not affect the heart rate across all tasks. The exoskeleton appeared to be more effective in tasks requiring substantial trunk flexion, indicating its potential benefits for reducing lower back muscle strain during such activities. [ABSTRACT FROM AUTHOR]

Accurately estimating knee joint angle during walking from surface electromyography (sEMG) signals can enable more natural control of wearable robotics like exoskeletons. However, challenges exist due to variability across individuals and sessions. This study evaluates an attention-based deep recurrent neural network combining gated recurrent units (GRUs) and an attention mechanism (AM) for knee angle estimation. Three experiments were conducted. First, the GRU-AM model was tested on four healthy adolescents, demonstrating improved estimation compared to GRU alone. A sensitivity analysis revealed that the key contributing muscles were the knee flexor and extensors, highlighting the ability of the AM to focus on the most salient inputs. Second, transfer learning was shown by pretraining the model on an open source dataset before additional training and testing on the four adolescents. Third, the model was progressively adapted over three sessions for one child with cerebral palsy (CP). The GRU-AM model demonstrated robust knee angle estimation across participants with healthy participants (mean RMSE 7 degrees) and participants with CP (RMSE 37 degrees). Further, estimation accuracy improved by 14 degrees on average across successive sessions of walking in the child with CP. These results demonstrate the feasibility of using attention-based deep networks for joint angle estimation in adolescents and clinical populations and support their further development for deployment in wearable robotics. [ABSTRACT FROM AUTHOR]

Purpose: This pilot study aimed to investigate the effects of REX exoskeleton rehabilitation robot training on the balance and lower limb function in patients with sub-acute stroke. Methods: This was a pilot, single-blind, randomized controlled trial. Twenty-four patients with sub-acute stroke (with the course of disease ranging from 3 weeks to 3 months) were randomized into two groups, including a robot group and a control group. Patients in control group received upright bed rehabilitation (n = 12) and those in robot group received exoskeleton rehabilitation robot training (n = 12). The frequency of training in both groups was once a day (60 min each) for 5 days a week for a total of 4 weeks. Besides, the two groups were evaluated before, 2 weeks after and 4 weeks after the intervention, respectively. The primary assessment index was the Berg Balance Scale (BBS), whereas the secondary assessment indexes included the Fugl-Meyer Lower Extremity Motor Function Scale (FMA-LE), the Posture Assessment Scale for Stroke Patients (PASS), the Activities of Daily Living Scale (Modified Barthel Index, MBI), the Tecnobody Balance Tester, and lower extremity muscle surface electromyography (sEMG). Results: The robot group showed significant improvements (P < 0.05) in the primary efficacy index BBS, as well as the secondary efficacy indexes PASS, FMA-LE, MBI, Tecnobody Balance Tester, and sEMG of the lower limb muscles. Besides, there were a significant differences in BBS, PASS, static eye-opening area or dynamic stability limit evaluation indexes between the robotic and control groups (P < 0.05). Conclusions: This is the first study to investigate the effectiveness of the REX exoskeleton rehabilitation robot in the rehabilitation of patients with stroke. According to our results, the REX exoskeleton rehabilitation robot demonstrated superior potential efficacy in promoting the early recovery of balance and motor functions in patients with sub-acute stroke. Future large-scale randomized controlled studies and follow-up assessments are needed to validate the current findings. Clinical trials registration: URL: https://www.chictr.org.cn/index.html.Unique identifier: ChiCTR2300068398. [ABSTRACT FROM AUTHOR]

In the process of exoskeleton design, the evaluation of assistance performance directly impacts the overall structural safety and efficiency. Addressing the current issue of predominantly utilizing single metrics for performance evaluation, a method based on multi‑source physiological signals (surface electromyography, photopretismography, and respiration) for LSTM prediction of motion energy consumption was proposed. This method involves preprocessing and feature extraction of physiological signals, followed by prediction using a 6‑layer LSTM model and validation through K-fold cross‑validation. Comparative experiments with DT and SVM were conducted. Finally, an online energy consumption monitoring system was established, serving as a basis for evaluating exoskeleton assistance performance. Results indicate the feasibility of utilizing multi‑source physiological signals for fusion prediction, with an RMSE of 0. 073 kJ for the three‑source signal. The LSTM model achieves a 39. 53% and 15. 68% reduction in RMSE compared to DT and SVM, respectively. The total energy consumption error on the test set is 23. 98 kJ, demonstrating the superior performance of the LSTM model for total energy consumption prediction and its suitability for exoskeleton assistance performance evaluation. [ABSTRACT FROM AUTHOR]

Decades of research determined electromyography (EMG) and electroencephalography (EEG), individually, as paramount controls aimed at rehabilitation. However, correlating commands from the central nervous system to lower-limb movements are highly complex raising challenges for anthropomorphic lower-limb prosthesis control. This work establishes a hierarchical relationship between 12-channel EEG and 4-channel surface EMG using a hybrid model (LRG-2L-LSTM) for lower-limb ankle movement recognition by estimating muscular activity from cortical brain signals. The proposed model achieved R2 = 0.742 ± 0.03, RMSE = 0.067 ± 0.002 for EMG estimation and averaged recognition accuracy of 84.86 ± 0.27% for ankle movements using estimated EMG, thereby, establishing lower-limb prosthesis and exoskeleton control for amputees with little to no muscular strength. [ABSTRACT FROM AUTHOR]

Back exosuits deliver mechanical assistance to reduce the risk of back injury, however, minimising restriction is critical for adoption. We developed the adaptive impedance controller to minimise restriction while maintaining assistance by modulating impedance based on the user's movement direction and nonlinear sine curves. The objective of this study was to compare active assistance, delivered by a back exosuit via our adaptive impedance controller, to three levels of assistance from passive elastics. Fifteen participants completed five experimental blocks (4 exosuits and 1 no-suit) consisting of a maximum flexion and a constrained lifting task. While a higher stiffness elastic reduced back extensor muscle activity by 13%, it restricted maximum range of motion (RoM) by 13°. The adaptive impedance approach did not restrict RoM while reducing back extensor muscle activity by 15%, when lifting. This study highlights an adaptive impedance approach might improve usability by circumventing the assistance-restriction trade-off inherent to passive approaches. Practitioner summary: This study demonstrates a soft active exosuit that delivers assistance with an adaptive impedance approach can provide reductions in overall back muscle activity without the impacts of restricted range of motion or perception of restriction and discomfort. [ABSTRACT FROM AUTHOR]

BACKGROUND: Long-term work with elevated arms, or overhead work, is a risk factor for musculoskeletal complaints and disorders. Upper-limb exoskeletons are a promising tool for reducing occupational workload when working with hands above shoulder level. OBJECTIVE: The purpose of this study was to assess the effects of upper-limb exoskeleton on muscular and physical strain and perceived exertion during dynamic work at four different shoulder joint angles. Further, we evaluated if there are any negative effects associated with the use of exoskeleton. METHODS: A total of 15 student participants performed dynamic work in laboratory setting with and without an exoskeleton at four different shoulder angles: 60, 90, 120 and 150 degrees. Muscle electrical activity from 8 muscles of the upper body, perceived exertion, and heart rate were measured during the work task, and grip strength, muscle stiffness, tone, and elasticity from six muscles, m. deltoideus physiological cross-sectional area and muscle fiber pennation angle, and nerve conduction velocity were measured before and after the work task. RESULTS: Based on the results, the use of exoskeleton significantly reduced the muscle activity of the upper limb, shoulder, and back muscles. The reduction was most significant when the arm elevation was 120°, and in m. deltoideus muscle activity. RPE was also positively affected indicating reduction in workload when using exoskeleton. CONCLUSION: The results suggest that the use of upper limb exoskeleton has potential to reduce physical workload during overhead work and, consequently, reduce the risk for work-related musculoskeletal disorders. [ABSTRACT FROM AUTHOR]

Background: Device-based rehabilitation of upper extremity impairment following stroke often employs one-sized-fits-all approaches that do not account for individual differences in patient characteristics. Objective: Determine if corticospinal tract lesion load could explain individual differences in the responsiveness to exoskeleton loading of the arms in chronic stroke participants. Methods: Fourteen stroke participants performed a bimanual shared cursor reaching task in virtual reality while exoskeletons decreased the effective weight of the more-impaired arm and increased the effective weight of the less-impaired arm. We calculated the change in relative displacement between the arms (RC) and the change in relative muscle activity (MC) between the arms from the biceps and deltoids. We calculated corticospinal tract lesion load (wCSTLL) in a subset of 10 participants. Results: Exoskeleton loading did not change RC (p = 0.07) or MC (p = 0.47) at the group level, but significant individual differences emerged. Participants with little overlap between the lesion and corticospinal tract responded to loading by decreasing muscle activity in the more-impaired arm relative to the less-impaired arm. The change in deltoid MC was associated with smaller wCSTLL (R² = 0.43, p = 0.039); there was no such relationship for biceps MC (R² < 0.001, p = 0.98). Conclusion: Here we provide evidence that corticospinal tract integrity is a critical feature that determines one’s ability to respond to upper extremity exoskeleton loading. Our work contributes to the development of personalized device-based interventions that would allow clinicians and researchers to titrate constraint levels during bimanual activities. [ABSTRACT FROM AUTHOR]

The design of human-machine interfaces of occupational exoskeletons is essential for their successful application, but at the same time demanding. In terms of information gain, biosensoric methods such as surface electromyography (sEMG) can help to achieve intuitive control of the device, for example by reduction of the inherent time latencies of a conventional, non-biosensoric, control scheme. To assess the reliability of sEMG onset detection under close to real-life circumstances, shoulder sEMG of 55 healthy test subjects was recorded during seated free arm lifting movements based on assembly tasks. Known algorithms for sEMG onset detection are reviewed and evaluated regarding application demands. A constant false alarm rate (CFAR) double-threshold detection algorithm was implemented and tested with different features. Feature selection was done by evaluation of signal-to-noise-ratio (SNR), onset sensitivity and precision, as well as timing error and deviation. Results of visual signal inspection by sEMG experts and kinematic signals were used as references. Overall, a CFAR algorithm with Teager-Kaiser-Energy-Operator (TKEO) as feature showed the best results with feature SNR = 14.48 dB, 91% sensitivity, 93% precision. In average, sEMG analysis hinted towards impending movements 215 ms before measurable kinematic changes. [ABSTRACT FROM AUTHOR]

Exoskeleton robots hold promising prospects for rehabilitation training in individuals with weakened muscular conditions. However, achieving improved human–machine interaction and delivering customized assistance remains a challenging task. This paper introduces a muscle synergy-based human-in-the-loop (HIL) optimization framework for hip exoskeletons to offer more personalized torque assistance. Initially, we propose a muscle synergy similarity index to quantify the similarity of synergy while walking with and without the assistance of an exoskeleton. By integrating surface electromyography (sEMG) signals to calculate metrics evaluating muscle synergy and iteratively optimizing assistance parameters in real time, a muscle synergy-based HIL optimized torque configuration is presented and tested on a portable hip exoskeleton. Iterative optimization explores the optimal and suboptimal assistance torque profiles for six healthy volunteers, simultaneously testing zero torque and predefined assistance configurations, and verified the corresponding muscle synergy similarity indices through experimental testing. In our validation experiments, the assistance parameters generated through HIL optimization significantly enhance muscle synergy similarity during walking with exoskeletal assistance, with an optimal average of 0.80 ± 0.04 (mean ± std), marking a 6.3% improvement over prior assistive studies and achieving 96.4% similarity compared with free walking. This demonstrates that the proposed muscle synergy-based HIL optimization can ensure robotic exoskeleton-assisted walking as "natural" as possible. [ABSTRACT FROM AUTHOR]

Objective: To evaluate using a back exoskeleton in a simulated sorting task in a static forward bent trunk posture on muscle activity, posture, and heart rate (HR). Background: Potentials of exoskeletons for reducing musculoskeletal demands in work tasks need to be clarified. Methods: Thirty-six healthy males performed the sorting task in 40°-forward bent static trunk posture for 90 seconds, in three trunk orientations, with and without exoskeleton. Muscle activity of the erector spinae (ES), biceps femoris (BF), trapezius descendens (TD), rectus abdominis (RA), vastus laterals (VL), and gastrocnemius medialis was recorded using surface electromyography normalized to a submaximal or maximal reference electrical activity (%RVE (reference voluntary electrical activity)/%MVE). Spine and lower limb postures were assessed by gravimetric position sensors, and HR by electrocardiography. Results: Using the exoskeleton resulted in decreased BF muscle activity [−8.12%RVE], and minor changes in ES [−1.29%MVE], RA [−0.28%RVE], VL [−0.49%RVE], and TD [+1.13%RVE] muscle activity. Hip and knee flexion increased [+8.1°; +6.7°]. Heart rate decreased by 2.1 bpm. Trunk orientation had an influence on BF muscle activity. Conclusion: Using the back exoskeleton in a short sorting task with static trunk posture mainly reduced hip extensor muscle activity and changed lower limb but not spine posture. Implications of using a back exoskeleton for workers' musculoskeletal health need further clarification. Application: The detected changes by using the Laevo® illustrate the need for further investigation prior to practical recommendations of using exoskeletons in the field. Investigating various work scenarios in different kind of workers and long-term applications would be important elements. [ABSTRACT FROM AUTHOR]

The introduction of exoskeletons in industry has focused on improving worker safety. Exoskeletons have the objective of decreasing the risk of injury or fatigue when performing physically demanding tasks. Exoskeletons' effect on the muscles is one of the most common focuses of their assessment. The present study aimed to analyze the muscle interactions generated during load-handling tasks in laboratory conditions with and without a passive lumbar exoskeleton. The electromyographic data of the muscles involved in the task were recorded from twelve participants performing load-handling tasks. The correlation coefficient, coherence coefficient, mutual information, and multivariate sample entropy were calculated to determine if there were significant differences in muscle interactions between the two test conditions. The results showed that muscle coordination was affected by the use of the exoskeleton. In some cases, the exoskeleton prevented changes in muscle coordination throughout the execution of the task, suggesting a more stable strategy. Additionally, according to the directed Granger causality, a trend of increasing bottom-up activation was found throughout the task when the participant was not using the exoskeleton. Among the different variables analyzed for coordination, the most sensitive to changes was the multivariate sample entropy. [ABSTRACT FROM AUTHOR]

Surface electromyography (sEMG) is widely used for analyzing and controlling lower limb assisted exoskeleton robots. Behavior intention recognition based on sEMG is of great significance for achieving intelligent prosthetic and exoskeleton control. Achieving highly efficient recognition while improving performance has always been a significant challenge. To address this,we propose an sEMG-basedmethod called EnhancedResidual GateNetwork (ERGN) for lower-limb behavioral intention recognition. The proposed network combines an attentionmechanism and a hard threshold function, while combining the advantages of residual structure, which maps sEMGofmultiple acquisition channels to the lower limbmotion states. Firstly, continuouswavelet transform(CWT) is used to extract signals features from the collected sEMG data. Then, a hard threshold function serves as the gate function to enhance signals quality, with an attention mechanism incorporated to improve the ERGN’s performance further. Experimental results demonstrate that the proposed ERGNachieves extremely high accuracy and efficiency,with an average recognition accuracy of 98.41% and an average recognition time of only 20ms-outperforming the state-ofthe- art research significantly. Our research provides support for the application of lower limb assisted exoskeleton robots. [ABSTRACT FROM AUTHOR]

In this study, a wearable exoskeleton with an active drive mechanism was designed for both space-saving and to ensure the safety and comfort of the workers. At the same time, this active wearable exoskeleton mechanism aims to facilitate the daily life of disabled people with its movement assisting feature. For these purposes, an active and wearable exoskeleton with a total of five degrees of freedom, two active (arm and shoulder flexion/extension) and three passive axes (shoulder lateral rotation and shoulder abduction/adduction), was developed. A novel load suspension system has been implemented to the design for absorbtion of the mechanism's own weight. The force-based impedance control method has been used for effective human–robot interaction. Furthermore, a low-cost electromyography sensor has been developed and integrated into the robotic system as biological feedback. As a result of the tests, it has been revealed that the system can help with lifting loads and successfully perform rehabilitation exercises. [ABSTRACT FROM AUTHOR]

Humans and animals navigate complex and variable terrain in day-to-day life. Wearable assistive exoskeletons interact with biological tissues to augment movement. Yet, our understanding of how these devices impact the biomechanics of movement beyond steady-state environments remains limited. We investigated how passive ankle exoskeletons influence mechanical energetics and neuromuscular control of the lower-limb during level, incline, and decline walking. We collected kinematic and kinetic measures to determine ankle, knee, and hip mechanics and surface electromyography to characterize muscle activation of lower-limb muscles while participants walked on level, incline, and decline surfaces (0°, +5°, and −5°) with exoskeletons of varying stiffnesses (0–280 Nm rad−1). Our results demonstrate that walking on incline surfaces with ankle exoskeletons was associated with increased negative work and power at the knee and increased positive work and power at the hip. These alterations in joint energetics may be linked to an additional requirement to load the springy exoskeleton in incline conditions. Decline walking with ankle exoskeletons had no influence on knee or hip energetics, likely owing to disrupted exoskeleton clutch actuation. To effectively offload the musculoskeletal system during walking on sloped surfaces, alterations to passive ankle exoskeleton clutch design are necessary. [ABSTRACT FROM AUTHOR]

Quantifying the trunk flexion angles at which wearable support systems (exoskeletons/exosuits) provide substantial trunk extension moment during posture maintenance tasks (such as those seen in surgical environments) can provide a deeper understanding of this potential intervention strategy. Understanding how time (i.e. adaptation/learning) might impact the reliance on wearable support is also of value. Sixteen participants were asked to maintain specific trunk flexion angles (range 0–60°) with and without an exosuit system while erector spinae and rectus abdominis muscle activity were captured using surface electromyography. The effects of the exosuit showed a statistically significant (p < 0.007) effect on the activity of the erector spinae muscles at 10–60°–an effect that became 'large' (Cohen's d = 0.84) after 20° of trunk flexion. There were no meaningful time-dependent trends in the levels of muscle activation indicating there was no adaptation/learning effect of the exosuit in the task studied. Practitioner summary: This study examined the effectiveness of a back-support exosuit as a function of trunk flexion angle and time of use. The results revealed that the exosuit significantly reduced erector spinae muscle activity beyond 20° of trunk flexion but did not show a meaningful adaption/learning effect. Abbreviations: LBP: low back pain; EMG: electromyography; NEMG: normalized electromyography; IMU: inertial measurement unit; ES: erector spinae; RA: rectus abdominis; MVC: maximum voluntary contraction; FFT: Fast Fourier Transform. [ABSTRACT FROM AUTHOR]

Abstract Background Electromyography (EMG) is a classical technique used to record electrical activity associated with muscle contraction and is widely applied in Biomechanics, Biomedical Engineering, Neuroscience and Rehabilitation Robotics. Determining muscle activation onset timing, which can be used to infer movement intention and trigger prostheses and robotic exoskeletons, is still a big challenge. The main goal of this paper was to perform a review of the state-of-the-art of EMG onset detection methods. Moreover, we compared the performance of the most commonly used methods on experimental EMG data. Methods A total of 156 papers published until March 2022 were included in the review. The papers were analyzed in terms of application domain, pre-processing method and EMG onset detection method. The three most commonly used methods [Single (ST), Double (DT) and Adaptive Threshold (AT)] were applied offline on experimental intramuscular and surface EMG signals obtained during contractions of ankle and knee joint muscles. Results Threshold-based methods are still the most commonly used to detect EMG onset. Compared to ST and AT, DT required more processing time and, therefore, increased onset timing detection, when applied on experimental data. The accuracy of these three methods was high (maximum error detection rate of 7.3%), demonstrating their ability to automatically detect the onset of muscle activity. Recently, other studies have tested different methods (especially Machine Learning based) to determine muscle activation onset offline, reporting promising results. Conclusions This study organized and classified the existing EMG onset detection methods to create consensus towards a possible standardized method for EMG onset detection, which would also allow more reproducibility across studies. The three most commonly used methods (ST, DT and AT) proved to be accurate, while ST and AT were faster in terms of EMG onset detection time, especially when applied on intramuscular EMG data. These are important features towards movement intention identification, especially in real-time applications. Machine Learning methods have received increased attention as an alternative to detect muscle activation onset. However, although several methods have shown their capability offline, more research is required to address their full potential towards real-time applications, namely to infer movement intention.

Recently, as modern people's consumption trends have been concentrated on contactless consumption such as online shopping since the 2019 COVID-19 Pandemic, the delivery industry, which is in charge of physical movement of online consumption activities, has also seen a series of utilization and demand. However, in contrast to the rapidly increasing volume of couriers, the labor environment of courier workers is poor, and the rapid increase in demand for courier service after the 2019 COVID-19 Pandemic has led to the rise in musculoskeletal diseases in courier workers. Various muscle support systems such as wearable robots have been developed to prevent musculoskeletal diseases in industrial sites, but the system is bulky, so the total weight is high, they are inconvenient to wear, and the wearers cannot freely perform activities when power is not supplied. In this study, the disadvantages of hard wearable robot systems, such as weight and power supply, were supplemented through elastic rubber bands and wires. In addition, wearable suits were developed to reduce the load on the body, prevent overwork, verify the effectiveness of work clothes, and prevent musculoskeletal diseases in courier workers. The experiment was conducted to verify whether the wearable suit affects muscle strength assistance by measuring the muscle usage when lifting weight after measuring the Maximum Voluntary Contract (MVC). The lifting types were classified into three types, and the strength assistance effects of the waist and lower extremities according to the wearable suit were compared. [ABSTRACT FROM AUTHOR]

BACKGROUND: Work-related musculoskeletal disorders (WMSDs) are a serious problem, and manual material handling (MMH) tasks remain common in most industries. Thus, a lightweight and active exoskeleton is needed. OBJECTIVE: A facile, convenient, multifunctional, wearable lumbar support exoskeleton (WLSE) was proposed to relieve the muscular tension and fatigue especially in the way of WMSDs. METHOD: Based on the screw theory and virtual power principle, the parallel structure was used as the scheme choice for selecting suitable actuators and joints. The exoskeleton, which was characterized by high adaptability and complied with human motion, included branch unit, mechanism branch units, control units and sensors. Furthermore, using surface electromyography (sEMG) signal evaluation, an experiment which contains several tests was designed to evaluate whether WLSE had effect on supporting and reliving muscular fatigue while lifting-up different weight of objects under wearing without traction (T1) and wearing with traction (T2). RESULTS: Data collected were analyzed statistically by the two-way ANOVA. It showed that the RMS of sEMG was obviously reduced while carrying the heavy objects with WLSE under T2, and the MF values always performed the decreasing trend in T2/T1. CONCLUSION: This paper proposed a facile, convenient, multifunctional WLSE. From the results, it was concluded that the WLSE was significantly effective in reliving the muscle tension and muscle fatigue while lifting to prevent and treat WMSDs. [ABSTRACT FROM AUTHOR]

Background: Electromyography (EMG) is a classical technique used to record electrical activity associated with muscle contraction and is widely applied in Biomechanics, Biomedical Engineering, Neuroscience and Rehabilitation Robotics. Determining muscle activation onset timing, which can be used to infer movement intention and trigger prostheses and robotic exoskeletons, is still a big challenge. The main goal of this paper was to perform a review of the state-of-the-art of EMG onset detection methods. Moreover, we compared the performance of the most commonly used methods on experimental EMG data. Methods: A total of 156 papers published until March 2022 were included in the review. The papers were analyzed in terms of application domain, pre-processing method and EMG onset detection method. The three most commonly used methods [Single (ST), Double (DT) and Adaptive Threshold (AT)] were applied offline on experimental intramuscular and surface EMG signals obtained during contractions of ankle and knee joint muscles. Results: Threshold-based methods are still the most commonly used to detect EMG onset. Compared to ST and AT, DT required more processing time and, therefore, increased onset timing detection, when applied on experimental data. The accuracy of these three methods was high (maximum error detection rate of 7.3%), demonstrating their ability to automatically detect the onset of muscle activity. Recently, other studies have tested different methods (especially Machine Learning based) to determine muscle activation onset offline, reporting promising results. Conclusions: This study organized and classified the existing EMG onset detection methods to create consensus towards a possible standardized method for EMG onset detection, which would also allow more reproducibility across studies. The three most commonly used methods (ST, DT and AT) proved to be accurate, while ST and AT were faster in terms of EMG onset detection time, especially when applied on intramuscular EMG data. These are important features towards movement intention identification, especially in real-time applications. Machine Learning methods have received increased attention as an alternative to detect muscle activation onset. However, although several methods have shown their capability offline, more research is required to address their full potential towards real-time applications, namely to infer movement intention. [ABSTRACT FROM AUTHOR]

Introduction: Research interest in exoskeleton assistance strategies that incorporate the user's torque capacity is growing rapidly. However, the predicted torque capacity fromusers often includes uncertainty fromvarious sources, which can have a significant impact on the safety of the exoskeleton-user interface. Methods: To address this challenge, this paper proposes an adaptive control framework for a knee exoskeleton that uses muscle electromyography (EMG) signals and joint kinematics. The framework predicted the user's knee flexion/extension torque with confidence bounds to quantify the uncertainty based on a neuromusculoskeletal (NMS) solver-informed Bayesian Neural Network (NMS-BNN). The predicted torque, with a specified confidence level, controlled the assistive torque provided by the exoskeleton through a TCP/IP stream. The performance of the NMS-BNN model was also compared to that of the Gaussian process (NMS-GP) model. Results: Our findings showed that both the NMS-BNN and NMS-GP models accurately predicted knee joint torque with low error, surpassing traditional NMS models. High uncertainties were observed at the beginning of each movement, and at terminal stance and terminal swing in self-selected speed walking in both NMS-BNN and NMS-GP models. The knee exoskeleton provided the desired assistive torque with a low error, although lower torque was observed during terminal stance of fast walking compared to self-selected walking speed. Discussion: The framework developed in this study was able to predict knee flexion/extension torque with quantifiable uncertainty and to provide adaptive assistive torque to the user. This holds significant potential for the development of exoskeletons that provide assistance as needed, with a focus on the safety of the exoskeleton-user interface. [ABSTRACT FROM AUTHOR]

Objective Low back pain (LBP) is hallmarked by activity limitations, especially for tasks involving bending. Back exosuit technology reduces low back discomfort and improves self-efficacy of individuals with LBP during bending and lifting tasks. However, the biomechanical efficacy of these devices in individuals with LBP is unknown. This study sought to determine biomechanical and perceptual effects of a soft active back exosuit designed to assist individuals with LBP sagittal plane bending. To understand patient-reported usability and use cases for this device. Methods Fifteen individuals with LBP performed two experimental lifting blocks once with and without an exosuit. Trunk biomechanics were measured by muscle activation amplitudes, and whole-body kinematics and kinetics. To evaluate device perception, participants rated task effort, low back discomfort, and their level of concern completing daily activities. Results The back exosuit reduced peak back extensor: moments by 9%, and muscle amplitudes by 16% when lifting. There were no changes in abdominal co-activation and small reductions maximum trunk flexion compared to lifting without an exosuit. Participants reported lower task effort, back discomfort, and concern about bending and lifting with an exosuit compared to without. Conclusions This study demonstrates a back exosuit not only imparts perceptual benefits of reduced task effort, discomfort, and increased confidence in individuals with LBP but that it achieves these benefits through measurable biomechanical reductions in back extensor effort. The combined effect of these benefits implies back exosuits might be a potential therapeutic aid to augment physical therapy, exercises, or daily activities. [ABSTRACT FROM AUTHOR]

One of the most difficult parts of stroke therapy is hand mobility recovery. Indeed, stroke is a serious medical disorder that can seriously impair hand and locomotor movement. To improve hand function in stroke patients, new medical technologies, such as various wearable devices and rehabilitation therapies, are being developed. In this study, a new design of electromyography (EMG)-controlled 3D-printed hand exoskeleton is presented. The exoskeleton was created to help stroke victims with their gripping abilities. Computer-aided design software was used to create the device's 3D architecture, which was then printed using a polylactic acid filament. For online classifications, the performance of two classifiers—the support vector machine (SVM) and the K-near neighbor (KNN)—was compared. The Robot Operating System (ROS) connects all the various system nodes and generates the decision for the hand exoskeleton. The selected classifiers had high accuracy, reaching up to 98% for online classification performed with healthy subjects. These findings imply that the new wearable exoskeleton, which could be controlled in accordance with the subjects' motion intentions, could aid in hand rehabilitation for a wider motion range and greater dexterity. [ABSTRACT FROM AUTHOR]

Musculoskeletal Disorders associated with the elboware one of themost common forms of work-related injuries. Exoskeletons have been proposed as an approach to reduce and ideally eliminate these injuries; however, exoskeletons introduce their own problems, especially discomfort due to joint misalignment. The Elbow-sideWINDER with its associated control strategy is a novel elbow exoskeleton to assist elbow flexion/extension during occupational tasks. This study describes the exoskeleton showing how this can minimize discomfort caused by joint misalignment, maximize assistive performance, and provide increased robustness and reliability in real worksites. The proposed medium-level control strategy can provide effective assistive torque using three control units as follows: an arm kinematics estimator, a load estimator, and a friction compensator. The combined hardware/software system of the Elbow-sideWINDER is tested in load-lifting tasks (2 and 7 kg). This experiment focuses on the reduction in the activation level of the biceps brachii and triceps brachii in both arms and the change in the range of motion of the elbowduring the task. It is shown that using the Elbow-sideWINDER, the biceps brachii, responsible for the elbowflexion, was significantly less activated (up to 38.8% at 2 kg and 25.7% at 7 kg, on average for both arms). For the triceps brachii, themuscle activation was reduced by up to 37.0%at 2 kg and 35.1%at 7 kg, on average for both arms. When wearing the exoskeleton, the range of motion of the elbowwas reduced by up to 13.0? during the task, but it was within a safe range and could be compensated for by other joints such as the waist or knees. There are extremely encouraging results that provide good indicators and important clues for future improvement of the Elbow-sideWINDER and its control strategy. [ABSTRACT FROM AUTHOR]

In recent years, the number of people with disabilities has increased hugely, especially in low- and middle-income countries. At the same time, robotics has made significant advances in the medical field, and many research groups have begun to develop low-cost wearable solutions. The Mechatronics and Dynamic Modelling Lab of the Department of Industrial Engineering at the University of Florence has recently developed a new version of a wearable hand exoskeleton for assistive purposes. In this paper, we will present a new regression method to predict the finger angle position of the first joint from the value of the sEMG of the forearm and the previous position of the finger itself. To acquire the dataset necessary to train the regressor a specific graphical user interface was developed which was able to acquire sEMG data from a Myo armband and the finger position from a Leap Motion Controller. Two long short-term memory (LSTM) models were compared, one in its standard configuration and the other with a convolutional layer, yielding significantly better performance for the second one, with an increase in R 2 coefficient from an average value of 0.746 to 0.825 , leading to the conclusion that a convolutional layer could increase performance when few sensors are available. [ABSTRACT FROM AUTHOR]

This paper presents the development of an instrumented exoskeleton with baropodometry, electromyography, and torque sensors. The six degrees of freedom (Dof) exoskeleton has a human intention detection system based on a classifier of electromyographic signals coming from four sensors placed in the muscles of the lower extremity together with baropodometric signals from four resistive load sensors placed at the front and rear parts of both feet. In addition, the exoskeleton is instrumented with four flexible actuators coupled with torque sensors. The main objective of the paper was the development of a lower limb therapy exoskeleton, articulated at hip and knees to allow the performance of three types of motion depending on the detected user's intention: sitting to standing, standing to sitting, and standing to walking. In addition, the paper presents the development of a dynamical model and the implementation of a feedback control in the exoskeleton. [ABSTRACT FROM AUTHOR]

Technology advancement has enabled the development of robotic exoskeletons that are portable, powerful, and sufficiently smart to be of practical use in the real world. These devices provide partial assistive forces that increase their user's physical strength to better meet the demands of everyday life and have potential applications in various settings. Examples include helping older adults maintain their independence and preventing musculoskeletal injuries among factory workers. Although great strides have been made to improve the performance and usability of these devices, human characteristics and the way humans adapt to the external assistive forces from these devices are rarely explicitly considered in their development. A common assumption is that if the provided assistive forces are aligned with the intent of users, users can easily "switch off" their muscles and effectively utilize this assistive force. In this review, we demonstrate that human adaptations to external assistive forces can lead to inefficiencies or conflicts that decrease the effectiveness of robotic exoskeletons. We then discuss the motor characteristics of human adaptations to external assistive forces. [ABSTRACT FROM AUTHOR]

Low-back pain is a major concern among healthcare workers. One cause is the frequent adoption of repetitive forward bent postures in their daily activities. Occupational exoskeletons have the potential to assist workers in such situations. However, their efficacy is largely task-dependent, and their biomechanical benefit in the healthcare sector has rarely been evaluated. The present study investigates the effects of a passive back support exoskeleton in a simulated patient bed bathing task. Nine participants performed the task on a medical manikin, with and without the exoskeleton. Results show that working with the exoskeleton induced a significantly larger trunk forward flexion, by 13 deg in average. Due to this postural change, using the exoskeleton did not affect substantially the muscular and cardiovascular demands nor the perceived effort. These results illustrate that postural changes induced by exoskeleton use, whether voluntary or not, should be considered carefully since they may cancel out biomechanical benefits expected from the assistance. Practitioner summary: Low-back pain is a major concern among nurses, associated with bent postures. We observed that using a passive back-support exoskeleton during the typical patient bed bathing activity results in a larger trunk flexion, without changing muscular, cardiovascular or perceived physical effort. [ABSTRACT FROM AUTHOR]

To analyse the versatility and adaptability of commercially available exoskeletons for mobility assistance and their adaptation to diverse pathologies through a review of clinical trials in robotic lower limb training. A computer-aided search in bibliographic databases (PubMed and Web of Science) of clinical trials published up to September 2020 was done. To be selected for detailed review, clinical trials had to meet the following criteria: (1) a protocol was designed and approved, (2) participants were people with pathologies, and (3) the trials were not a single case study. Clinical trial data were collected, extracted, and analysed, considering: objectives, trial participants, number of sessions, pathologies involved, and conclusions. The search resulted in 312 potentially relevant studies of seven commercial exoskeletons, of which 135 passed the preliminary screening; and 69 studies were finally selected. Of the 69 clinical trials included in the review about 50% involved Spinal Cord Injury participants, while roughly 25% focussed on stroke and two trials corresponded to patients with both disorders. The rest were composed of neurological diseases and trauma disorders. The use of a single wearable robot for different medical conditions in various diseases is a challenge. Based on this comparative, the properties of the exoskeletons that improve the working ability with different pathologies and patient conditions have been evaluated. Suggestions were made for developing a new lower-limb exoskeleton based on various modules with a distributed control system to improve versatility in wearable technology for different gait pattern progression. Wearable robotic exoskeletons for gait assistance have been analysed from the perspective of adaptation to different diseases. This paper emphasizes the importance of personalized therapies and adaptive assistive technology. Suggestions were made for a new modular exoskeleton capable of addressing the issue of low versatility characterizing currently wearable assistive technology. [ABSTRACT FROM AUTHOR]

The rehabilitation of children with motor disorders is mainly focused on physical interventions. Numerous studies have demonstrated the benefits of upper function using robotic exoskeletons. However, there is still a gap between research and clinical practice, owing to the cost and complexity of these devices. This study presents a proof of concept of a 3D-printed exoskeleton for the upper limb, following a design that replicates the main characteristics of other effective exoskeletons described in the literature. 3D printing enables rapid prototyping, low cost, and easy adjustment to the patient anthropometry. The 3D-printed exoskeleton, called POWERUP, assists the user’s movement by reducing the effect of gravity, thereby allowing them to perform upper limb exercises. To validate the design, this study performed an electromyography-based assessment of the assistive performance of POWERUP, focusing on the muscular response of both the biceps and triceps during elbow flexion–extension movements in 11 healthy children. The Muscle Activity Distribution (MAD) is the proposed metric for the assessment. The results show that (1) the exoskeleton correctly assists elbow flexion, and (2) the proposed metric easily identifies the exoskeleton configuration: statistically significant differences (p-value = 2.26 ⋅ 10−7 < 0.001) and a large effect size (Cohen’s d = 3.78 > 0.8) in the mean MAD value were identified for both the biceps and triceps when comparing the transparent mode (no assistance provided) with the assistive mode (anti-gravity effect). Therefore, this metric was proposed as a method for assessing the assistive performance of exoskeletons. Further research is required to determine its usefulness for both the evaluation of selective motor control (SMC) and the impact of robot-assisted therapies. [ABSTRACT FROM AUTHOR]

Wearable exoskeletons play an important role in people's lives, such as helping stroke and amputation patients to carry out rehabilitation training and so on. How to make the exoskeleton accurately judge the human action intention is the basic requirement to ensure that it can complete the corresponding task. Traditional exoskeleton control signals include pressure values, joint angles and acceleration values, which can only reflect the current motion information of the human lower limbs and cannot be used to predict motion. The electromyography (EMG) signal always occurs before a certain movement; it can be used to predict the target's gait speed and movement as the input signal. In this study, the generalization ability of a BP neural network and the timing property of a hidden Markov chain are used to properly fuse the two, and are finally used in the research of this paper. Experiments show that, using the same training samples, the recognition accuracy of the three-layer BP neural network is only 91%, while the recognition accuracy of the fusion discriminant model proposed in this paper can reach 95.1%. The results show that the fusion of BP neural network and hidden Markov chain has a strong solving ability for the task of wearable exoskeleton recognition of target step speed. [ABSTRACT FROM AUTHOR]

The effectiveness of EMG biofeedback with neurorehabilitation robotic platforms has not been previously addressed. The present work evaluates the influence of an EMG-based visual biofeedback on the user performance when performing EMG-driven bilateral exercises with a robotic hand exoskeleton. Eighteen healthy subjects were asked to perform 1-min randomly generated sequences of hand gestures (rest, open and close) in four different conditions resulting from the combination of using or not (1) EMG-based visual biofeedback and (2) kinesthetic feedback from the exoskeleton movement. The user performance in each test was measured by computing similarity between the target gestures and the recognized user gestures using the L2 distance. Statistically significant differences in the subject performance were found in the type of provided feedback (p-value 0.0124). Pairwise comparisons showed that the L2 distance was statistically significantly lower when only EMG-based visual feedback was present (2.89 ± 0.71) than with the presence of the kinesthetic feedback alone (3.43 ± 0.75, p-value = 0.0412) or the combination of both (3.39 ± 0.70, p-value = 0.0497). Hence, EMG-based visual feedback enables subjects to increase their control over the movement of the robotic platform by assessing their muscle activation in real time. This type of feedback could benefit patients in learning more quickly how to activate robot functions, increasing their motivation towards rehabilitation. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effect of using a passive back-support exoskeleton (Laevo V2.56) on muscle activity, posture, heart rate, performance, usability, and wearer comfort during a course of three industrial tasks (COU; exoskeleton worn, turned-on), stair climbing test (SCT; exoskeleton worn, turned-off), timed-up-and-go test (TUG; exoskeleton worn, turned-off) compared to no exoskeleton. Background: Back-support exoskeletons have the potential to reduce work-related physical demands. Methods: Thirty-six men participated. Activity of erector spinae (ES), biceps femoris (BF), rectus abdominis (RA), vastus lateralis (VL), gastrocnemius medialis (GM), trapezius descendens (TD) was recorded by electromyography; posture by trunk, hip, knee flexion angles; heart rate by electrocardiography; performance by time-to-task accomplishment (s) and perceived task difficulty (100-mm visual analogue scale; VAS); usability by the System Usability Scale (SUS) and all items belonging to domains skepticism and user-friendliness of the Technology Usage Inventory; wearer comfort by the 100-mm VAS. Results: During parts of COU, using the exoskeleton decreased ES and BF activity and trunk flexion, and increased RA, GM, and TD activity, knee and hip flexion. Wearing the exoskeleton increased time-to-task accomplishment of SCT, TUG, and COU and perceived difficulty of SCT and TUG. Average SUS was 75.4, skepticism 11.5/28.0, user-friendliness 18.0/21.0, wearer comfort 31.1 mm. Conclusion: Using the exoskeleton modified muscle activity and posture depending on the task applied, slightly impaired performance, and was evaluated mildly uncomfortable. Application: These outcomes require investigating the effects of this passive back-supporting exoskeleton in longitudinal studies with longer operating times, providing better insights for guiding their application in real work settings. [ABSTRACT FROM AUTHOR]

Powered exoskeletons need actuators that are lightweight, compact, and efficient while allowing for accurate torque control. To satisfy these requirements, researchers have proposed using series elastic actuators (SEAs). SEAs use a spring in series with rotary or linear actuators. The spring compliance, in conjunction with an appropriate control scheme, improves torque control, efficiency, output impedance, and disturbance rejection. However, springs add weight to the actuator and complexity to the control, which may have negative effects on the performance of the powered exoskeleton. Therefore, there is an unmet need for new SEA designs that are lighter and more efficient than available systems, as well as for control strategies that push the performance of SEA-based exoskeletons without requiring complex modeling and tuning. This article presents the design, development, and testing of a novel SEA with high force density for powered exoskeletons, as well as the use of a two degree-of-freedom (2DOF) PID system to improve output impedance and disturbance rejection. Benchtop testing results show reduced output impedance and damping values when using a 2DOF PID controller as compared to a 1DOF PID controller. Human experiments with three able-bodied subjects (N = 3) show improved torque tracking with reduced root-mean-square error by 45.2% and reduced peak error by 49.8% when using a 2DOF PID controller. Furthermore, EMG data shows a reduction in peak EMG value when using the exoskeleton in assistive mode compared to the exoskeleton operating in transparent mode. [ABSTRACT FROM AUTHOR]

Shoulder exoskeletons (SEs) can assist the shoulder joint of workers during overhead work and are usually passive for good portability. However, current passive SEs face the challenge that their torque generators are often attached to the human arm, which adds a significant amount of weight to the user’s arms, resulting in additional energy consumption of the user. In this paper, we present a novel passive SE whose torque generator is attached to the user’s back and assists the shoulder joint through Bowden cables. Our approach greatly reduces the weight on the user’s arms and can accommodate complex shoulder joint movements with simple and lightweight mechanical structure based on Bowden cables. In addition, to match the nonlinear torque requirements of the shoulder joint, a unique spring-cam mechanism is proposed as the torque generator. To verify the effectiveness of the device, we conducted a usability test based on muscle activations of 10 healthy subjects. When assisting overhead work, the SE significantly reduced the mean and maximum electromyography signals of the shoulder-related muscles by up to 25%. The proposed SE contributes to further research on passive SE design to improve usability, especially in terms of reducing weight on human arms. [ABSTRACT FROM AUTHOR]

Evaluating exoskeleton actuation methods and designing an effective controller for these exoskeletons are both challenging and time-consuming tasks. This is largely due to the complicated human–robot interactions, the selection of sensors and actuators, electrical/command connection issues, and communication delays. In this research, a test framework for evaluating a new active–passive shoulder exoskeleton was developed, and a surface electromyography (sEMG)-based human-robot cooperative control method was created to execute the wearer’s movement intentions. The hierarchical control used sEMG-based intention estimation, mid-level strength regulation, and low-level actuator control. It was then applied to shoulder joint elevation experiments to verify the exoskeleton controller’s effectiveness. The active–passive assistance was compared with fully passive and fully active exoskeleton control using the following criteria: (1) post-test survey, (2) load tolerance duration, and (3) computed human torque, power, and metabolic energy expenditure using sEMG signals and inverse dynamic simulation. The experimental outcomes showed that active–passive exoskeletons required less muscular activation torque (50%) from the user and reduced fatigue duration indicators by a factor of 3, compared to fully passive ones. [ABSTRACT FROM AUTHOR]

Musculoskeletal disorders constitute the leading work-related health issue. Mechanical loading of the lower back contributes as a major risk factor and is prevalent in many tasks performed in logistics. The study aimed to compare acute effects of exoskeletons with different functional mechanisms in a logistic task. Twelve young, healthy individuals participated in the study. Five exoskeletons with different functional mechanisms were tested in a logistic task, consisting of lifting, carrying, and lowering a 13 kg box. By using electromyography (EMG), mean muscle activities of four muscles in the trunk were analyzed. Additionally, kinematics by task completion time and range of motion (RoM) of the major joints and segments were investigated. A main effect was found for Musculus erector spinae, Musculus multifidus, and Musculus latissimus dorsi showing differences in muscle activity reductions between exoskeletons. Reduction in ES mean activity compared to baseline was primarily during lifting from ground level. The exoskeletons SoftExo Lift and Cray X also showed ES mean reduction during lowering the box. Prolonged task duration during the lifting phase was found for the exoskeletons BionicBack, SoftExo Lift, and Japet.W. Japet.W showed a trend in reducing hip RoM during that phase. SoftExo Lift caused a reduction in trunk flexion during the lifting phase. A stronger trunk inclination was only found during lifting from the table for the SoftExo Lift and the Cray X. In conclusion, muscle activity reductions by exoskeleton use should not be assessed without taking their designed force paths into account to correctly interpret the effects for long-term injury prevention. [ABSTRACT FROM AUTHOR]

Soft exosuits offer promise to support users in everyday workload tasks by providing assistance. However, acceptance of such systems remains low due to the difficulty of control compared with rigid mechatronic systems. Recently, there has been progress in developing control schemes for soft exosuits that move in line with user intentions. While initial results have demonstrated sufficient device performance, the assessment of user experience via the cognitive response has yet to be evaluated. To address this, we propose a soft pneumatic elbow exosuit designed based on our previous work to provide assistance in line with user expectations utilizing two existing state-of-the-art control methods consisting of a gravity compensation and myoprocessor based on muscle activation. A user experience study was conducted to assess whether the device moves naturally with user expectations and the potential for device acceptance by determining when the exosuit violated user expectations through the neuro-cognitive and motor response. Brain activity from electroencephalography (EEG) data revealed that subjects elicited error-related potentials (ErrPs) in response to unexpected exosuit actions, which were decodable across both control schemes with an average accuracy of 76.63 ± 1.73% across subjects. Additionally, unexpected exosuit actions were further decoded via the motor response from electromyography (EMG) and kinematic data with a grand average accuracy of 68.73 ± 6.83% and 77.52 ± 3.79% respectively. This work demonstrates the validation of existing state-of-the-art control schemes for soft wearable exosuits through the proposed soft pneumatic elbow exosuit. We demonstrate the feasibility of assessing device performance with respect to the cognitive response through decoding when the device violates user expectations in order to help understand and promote device acceptance. [ABSTRACT FROM AUTHOR]

Human-in-the-loop (HITL) optimization with metabolic cost feedback has been proposed to reduce walking effort with wearable robotics. This study investigates if lower limb surface electromyography (EMG) could be an alternative feedback variable to overcome time-intensivemetabolic cost based exploration. For application, it should be possible to distinguish conditions with different walking efforts based on the EMG. To obtain such EMG data, a laboratory experiment was designed to elicit changes in the effort by loading and unloading pairs of weights (in total 2, 4, and 8 kg) in three randomized weight sessions for 13 subjects during treadmill walking. EMG of seven lower limb muscles was recorded for both limbs. Mean absolute values of each stride prior to and following weight loading and unloading were used to determine the detection rate (100% if every loading and unloading is detected accordingly) for changing between loaded and unloaded conditions. We assessed the use of multiple consecutive strides and the combination of muscles to improve the detection rate and estimated the related acquisition times of diminishing returns. To conclude on possible limitations of EMG for HITL optimization, EMG drift was evaluated during the Warmup and the experiment. Detection rates highly increased for the combination of multiple consecutive strides and the combination of multiple muscles. EMG drift was largest duringWarmup and at the beginning of each weight session. The results suggest using EMG feedback of multiple involved muscles and from at least 10 consecutive strides (5.5 s) to benefit from the increases in detection rate in HITL optimization. In combination with up to 20 excluded acclimatization strides, after changing the assistance condition, we advise exploring about 16.5 s of walking to obtain reliable EMG-based feedback. To minimize the negative impact of EMG drift on the detection rate, at least 6 min of Warmup should be performed and breaks during the optimization should be avoided. Future studies should investigate additional feedback variables based on EMG, methods to reduce their variability and drift, and should apply the outcomes in HITL optimization with lower limb wearable robots. [ABSTRACT FROM AUTHOR]

Objective: This paper assesses the effect of a passive shoulder exoskeleton prototype, Exo4Work, on muscle activity, muscle fatigue and subjective experience during simulated occupational overhead and non-overhead work. Methods: Twenty-two healthy males performed six simulated industrial tasks with and without Exo4Work exoskeleton in a randomized counterbalanced cross-over design. During these tasks electromyography, heart rate, metabolic cost, subjective parameters and performance parameters were acquired. The effect of the exoskeleton and the body side on these parameters was investigated. Results: Anterior deltoid activity and fatigue reduced up to 16% and 41%, respectively, during isometric overhead work, and minimized hindrance of the device during non-overhead tasks. Wearing the exoskeleton increased feelings of frustration and increased discomfort in the areas where the exoskeleton and the body interfaced. The assistive effect of the exoskeleton was less prominent during dynamic tasks. Conclusion: This exoskeleton may reduce muscle activity and delay development of muscle fatigue in an overhead working scenario. For dynamic applications, the exoskeleton’s assistive profile, which mimics the gravitational torque of the arm, is potentially sub-optimal. Significance: This evaluation paper is the first to report reduced muscle fatigue and activity when working with an occupational shoulder exoskeleton providing one third of the gravitational torque of the arm during overhead work. These results stress the potential of occupational shoulder exoskeletons in overhead working situations and may direct towards longitudinal field experiments. Additionally, this experiment may stimulate future work to further investigate the effect of different assistive profiles. [ABSTRACT FROM AUTHOR]

An FDA-approved soft wearable robot, the Myosuit, which was designed to provide hip and knee extension torque has recently been commercialized. While studies have reported reductions in metabolic costs, increased gait speeds, and improvements in clinical test scores, a comprehensive analysis of electromyography (EMG) signals and joint kinematics is warranted because the recruitment of appropriate muscle groups during physiological movement patterns facilitates effective motor learning. Here, we compared the lower limb joint kinematics and EMG patterns while wearing the Myosuit with that of unassisted conditions when performing level overground and incline treadmill gait. The level overground gait sessions (seven healthy subjects) were performed at self-selected speeds and the incline treadmill gait sessions (four healthy subjects) were performed at 2, 3, 4, and 5 km/h. In order to evaluate how the user is assisted, we conducted a biomechanical analysis according to the three major gait tasks: weight acceptance (WA), single-limb support, and limb advancement. The results from the gait sessions suggest that Myosuit not only well preserves the users' natural patterns, but more importantly reduce knee extensor demand during the WA phase for both level and incline gait. [ABSTRACT FROM AUTHOR]

Objective: Many individuals with cerebral palsy (CP) experience gait deficits resulting in metabolically-inefficient ambulation that is exacerbated by graded walking terrains. The primary goal of this study was to clinically-validate the accuracy and efficacy of adaptive ankle exoskeleton assistance during steady-state incline walking and stair ascent in individuals with CP. Exploratory goals were to assess safety and feasibility of using adaptive ankle exoskeleton assistance in real-world mixed-terrain settings. Methods: We used a novel battery-powered ankle exoskeleton to provide adaptive ankle plantar-flexor assistance during stance phase. Seven ambulatory individuals with CP completed the study. Results: Adaptive controller accuracy was 85% for incline walking and 81% for stair-stepping relative to the biological ankle moment. Assistance improved energy cost of steady-state incline walking by 14% (p = 0.004) and stair ascent by 21% (p = 0.001) compared to walking without the device. Assistance reduced the muscular demand for the soleus and vastus lateralis during both activities. All participants were able to safely complete the real-world mixed-terrain route, with adaptive ankle assistance resulting in improved outcomes compared to walking with the device providing zero-torque; no group-level differences were found compared to walking without the device, yet individuals with more impairment exhibited a marked improvement. Conclusion: Adaptive ankle exoskeleton assistance can improve the energy cost of steady-state incline walking and stair ascent in individuals with CP. Significance: As the first study to demonstrate safety and performance benefits of ankle assistance on graded terrains in CP, these findings encourage further investigation in free-living settings. [ABSTRACT FROM AUTHOR]

To prevent lower back pain (LBP) in the industrial workplace, various powered back support exoskeletons (BSEs) have been developed. However, conventional kinematics-triggered assistance (KA) strategies induce latency, degrading assistance efficiency. Therefore, we proposed and experimentally evaluated a surface electromyography (sEMG)-triggered assistance (EA) strategy. Nine healthy subjects participated in the lifting experiments: 1) external loads test, 2) extra latency test, and 3) repetitive lifting test. In the external loads test, subject performed lifting with four different external loads (0 kg, 7.5 kg, 15 kg, and 22.5 kg). The assistance was triggered earlier by EA compared to KA from 114 ms to 202 ms, 163 ms to 269 ms for squat and stoop lifting respectively, as external loads increased from 0 kg to 22.5 kg. In the extra latency test, the effects of extra latency (manual switch, 0 ms, 100 ms and 200 ms) in EA on muscle activities were investigated. Muscle activities were minimized in the fast assistance (0 ms and 100 ms) condition and increased with extra latency. In the repetitive lifting test, the EA strategy significantly reduced L1 muscle fatigue by 70.4% in stoop lifting, compared to KA strategy. Based on the experimental results, we concluded that fast assistance triggered by sEMG improved assistance efficiency in BSE and was particularly beneficial in heavy external loads situations. The proposed assistive strategy can be used to prevent LBP by reducing back muscle fatigue and is easily applicable to various industrial exoskeleton applications. [ABSTRACT FROM AUTHOR]

Functional electrical stimulation (FES) can be used to initiate lower limb muscle contractions and has been widely applied in gait rehabilitation. Establishing the correct timing of FES activation during each phase of the gait (walking) cycle remains challenging as most FES systems rely on open-loop control, whereby the controller receives no feedback about joint kinematics and instead relies on predetermined/timed muscle stimulation. The objective of this study was to develop and validate a closed-loop FES-based control solution for gait rehabilitation using a finite state machine (FSM) model. A two-phased study approach was taken: (1) Experimentally-Informed Study: A neuromuscular-derived FSM model was developed to drive closed-loop FES-based control for gait rehabilitation. The finite states were determined using electromyography and joint kinematics data of 12 non-disabled adults, collected during treadmill walking. The gait cycles were divided into four states, namely: swing-to-stance, push off, pre-swing, and toe up. (2) Simulation Study: A closed-loop FES-based control solution that employed the resulting FSM model, was validated through comparisons of neuro-musculo-skeletal computer simulations of impaired versus healthy gait. This closed-loop controller yielded steadier simulated impaired gait, in comparison to an open-loop alternative. The simulation results confirmed that accurate timing of FES activation during the gait cycle, as informed by kinematics data, is important to natural gait retraining. The closed-loop FES-based solution, introduced in this study, contributes to the repository of gait rehabilitation control options and offers the advantage of being simplistic to implement. Furthermore, this control solution is expected to integrate well with powered exoskeleton technologies. [ABSTRACT FROM AUTHOR]