A Pilot Study of Varying Thoracic and Abdominal Compression in a Reconfigurable Trunk Exoskeleton During Different Activities

Evaluation of the support provided by a soft passive exoskeleton in individuals with back pain

Physically straining occupations involving repetitive lifting and forward leaning increase risk of back pain. In response, back exoskeletons have been developed to alleviate strain on back muscles and potentially prevent such pain. In people experiencing back pain, these may also help decrease the pain-related activity limitations during work or leisure. This experimental study evaluated the effects of a soft passive back exoskeleton on muscle activity, acute pain, kinesiophobia, and movement kinematics. Individuals experiencing mild to moderate back pain (n=35) performed forward leaning and lifting tasks, both with and without the support of the back exoskeleton. Electromyography data were collected for trunk and hip muscles, alongside hip and spine kinematics, reported pain levels and concerns regarding daily activities. Back exoskeleton support reduced back muscle activity during forward leaning by up to 35% (pExo<0.001) and during lifting tasks by up to 24% (pExo<0.001). Participants reported reduced lumbar pain (p<0.01) and decreased kinesiophobia (p<0.001) across all tasks when supported by the exoskeleton. Minimal influence on movement kinematics was observed and there were no observable changes in abdominal co-activation compared to tasks performed without exoskeleton support. These results indicate that the LiftSuit, a passive back exoskeleton, can effectively reduce back muscle activity, acute pain, and kinesiophobia among individuals with back pain during forward leaning and repetitive lifting tasks. These findings suggest that passive back exoskeletons may be beneficial during physically demanding tasks in workers experiencing mild to moderate back pain.

A comprehensive assessment of a passive back support exoskeleton for load handling assistance

Various back support exoskeletons (BSEs) have been developed to reduce the workload and the risk of musculoskeletal disorders. However, the evaluations of such devices have primarily focused on specific quantitative aspects like muscle activation level or metabolic cost without any assessment of the user perception or comfort. In addition, the absence of an universal guidance or agreement on the methods for quantifying the efficacy of exoskeletons has hampered a systematic comparison among the developed devices. This study introduces a newly developed passive BSE for heavy load handling workers, and verifies its assistive effect through a rigorous and multifaceted evaluation. Fifteen young and healthy males participated in two experiment sessions. In the first session, participants lifted a 15 kg box and held it in a static position. In the second session, participants performed repetitive lifting tasks with a 10 kg box. The developed BSE reduced root mean square, peak, and integrated muscle activation with statistical significance in the key muscles. The BSE alleviated muscle fatigue by delaying spectral shift of instantaneous median frequency in the lumbar erector spinae (p < 0.001) and gluteus maximus (p < 0.001). The BSE also decreased energy expenditure by 13.6% (p < 0.001). In addition, the BSE reduced participants' rate of perceived exertion and local musculoskeletal discomfort by 14.7% (p = 0.005) and 30.5% (p = 0.001), respectively. These results support the efficacy of the developed BSE. The multifaceted evaluation process used in this study also contributes to proposing a systematic guidance on evaluating BSEs.

Benchmarking commercially available soft and rigid passive back exoskeletons for an industrial workplace

Low-back pain is a common occupational hazard for industrial workers. Several studies show the advantages of using rigid and soft back-support passive exoskeletons and exosuits (exos) to reduce the low-back loading and risk of injury. However, benefits of using these exos have been shown to be task-specific. Therefore, in this study, we developed a benchmarking approach to assess exos for an industrial workplace at Hankamp Gears B.V. We assessed two rigid (Laevo Flex, Paexo back) and two soft (Auxivo Liftsuit 1.0, and Darwing Hakobelude) exos for tasks resembling the workplace. We measured the assistive moment provided by each exo and their respective influence on muscle activity as well as the user's perception of comfort and exertion. Ten participants performed four lifting tasks (Static hold, Asymmetric, Squat, and Stoop), while their electromyography and subjective measures were collected. The two rigid exos provided the largest assistance during the Dynamic tasks. Reductions in erector spinae activity were seen to be task-specific, with larger reductions for the two rigid exos. Overall, Laevo Flex offered a good balance between assistive moments, reductions in muscle activity, as well as user comfort and reductions in perceived exertion. Thus, we recommend benchmarking exos for intended use in the industrial workplace. This will hopefully result in a better adoption of the back-support exoskeletons in the workplace and help reduce low-back pain.

Effects of the Auxivo CarrySuit occupational exoskeleton when carrying front and side loads on a treadmill

Low-cost exoskeletons can effectively support workers in physically demanding jobs, but most such exoskeletons have been developed to support repetitive lifting or uncomfortable static postures. Very few low-cost exoskeletons have been designed to support walking while carrying heavy objects, which would be beneficial for jobs such as moving furniture and warehouse work. This paper thus presents a single-session lab evaluation of the Auxivo CarrySuit, a low-cost upper-body exoskeleton designed for carrying objects that would normally be held with the arms. Twenty participants carried four loads (box or two bags, 20 or 40 lb total weight) for 2 min each on a treadmill with and without the CarrySuit. Across all loads, the CarrySuit significantly reduced the mean electromyogram of the middle trapezius (partial eta-squared = 0.74 - from 16.1% to 8.8% of maximum voluntary contraction value) and anterior deltoid (partial eta-squared = 0.26 - from 3.0% to 1.1% of maximum voluntary contraction value) with no corresponding increase in lower back muscle activation. Furthermore, maximum heart rate and Ratings of Perceived Exertion were also reduced by the CarrySuit, and discomfort was shifted from the upper body to the legs. While arm EMG was not measured, it is likely that it was also reduced due to the unloading of the arms. The CarrySuit can thus be considered beneficial in the short term, though longer-term evaluations with actual workers are needed to determine practical benefits.

Short-term effects of the Auxivo LiftSuit during lifting and static leaning

Back support exosuits can support workers in physically demanding jobs by reducing muscle load, which could reduce risk of work-related musculoskeletal disorders. This paper presents a two-session evaluation of a commercial exosuit, the Auxivo LiftSuit 1.1. In session 1, 17 participants performed single repetitions of lifting and static leaning tasks with and without the LiftSuit. In session 2, 10 participants performed 50 box lifting repetitions with and without the LiftSuit. In session 1, the exosuit was considered mildly to moderately helpful, and reduced erector spinae and middle trapezius electromyograms. In session 2, the exosuit was not considered helpful, but reduced the middle trapezius electromyogram and trunk and thigh ranges of motion. These effects are likely due to placement of elastic elements and excessive stiffness at the hips. Overall, the LiftSuit appears suboptimal for long-term use, though elastic elements on the upper back may reduce muscle activation in future exosuit designs.

Study on the Effects of Different Seat and Leg Support Conditions of a Trunk Rehabilitation Robot

Performance of trunk rehabilitation exercises while sitting on movable surfaces with feet on the ground can increase trunk and leg muscle activations, and constraining the feet to move with the seat isolates control of the trunk. However, there are no detailed studies on the effects of these different leg supports on the trunk and leg muscle activations under unstable and forcefully perturbed seating conditions. We have recently devised a trunk rehabilitation robot that can generate unstable and forcefully perturbed sitting surfaces, and can be used with ground-mounted or seat-connected footrests. In this study, we have evaluated the differences in balance performance, trunk movement and muscle activation (trunk and legs) of fourteen healthy adults caused by the use of these different footrest configurations under the different seating scenarios. The center of pressure and trunk movement results show that the seat-connected footrest may be a more suitable choice for use in a balance recovery focused rehabilitation protocol, while the ground-mounted footrest may be a more suitable choice for a trunk movement focused rehabilitation protocol. Although it is difficult to make a clear selection between footrests due to the mixed trends observed in the muscle activation results, it appears that the seat-connected footrest may be preferable for use with the unstable seat as it causes greater muscle activations. Furthermore, the results provide limited evidence that targeting of a particular muscle group may be possible through careful selection of the seat and footrest conditions. Therefore, it may be possible to utilize the trunk rehabilitation robot to maximize the training outcomes for a wide range of patients through careful selection of training protocols.

Challenges and solutions for application and wider adoption of wearable robots

The science and technology of wearable robots are steadily advancing, and the use of such robots in our everyday life appears to be within reach. Nevertheless, widespread adoption of wearable robots should not be taken for granted, especially since many recent attempts to bring them to real-life applications resulted in mixed outcomes. The aim of this article is to address the current challenges that are limiting the application and wider adoption of wearable robots that are typically worn over the human body. We categorized the challenges into mechanical layout, actuation, sensing, body interface, control, human-robot interfacing and coadaptation, and benchmarking. For each category, we discuss specific challenges and the rationale for why solving them is important, followed by an overview of relevant recent works. We conclude with an opinion that summarizes possible solutions that could contribute to the wider adoption of wearable robots.

Simultaneously varying back stiffness and trunk compression in a passive trunk exoskeleton during different activities: A pilot study

Passive trunk exoskeletons support the human body with mechanical elements like springs and trunk compression, allowing them to guide motion and relieve the load on the spine. However, to provide appropriate support, elements of the exoskeleton (e.g., degree of compression) should be intelligently adapted to the current task. As it is not currently clear how adjusting different exoskeleton elements affects the wearer, this study preliminarily examines the effects of simultaneously adjusting both exoskeletal spinal column stiffness and trunk compression in a passive trunk exoskeleton. Six participants performed four dynamic tasks (walking, sit-to-stand, lifting a 20-lb box, lifting a 40-lb box) and experienced unexpected perturbations both without the exoskeleton and in six exoskeleton configurations corresponding to two compression levels and three stiffness levels. While results are preliminary due to the small sample size and relatively small increases in stiffness, they indicate that both compression and stiffness may affect kinematics and electromyography, that the effects may differ between activities, and that there may be interaction effects between stiffness and compression. As the next step, we will conduct a larger study with the same protocol more participants and larger stiffness increases to systematically evaluate the effects of different exoskeleton characteristics on the wearer.Clinical Relevance- Trunk exoskeletons can support wearers during a variety of different tasks, but their configuration may need to be intelligently adjusted to provide appropriate support. This pilot study provides information about the effects of exoskeleton back stiffness and trunk compression on the wearer, which can be used as a basis for more effective device design and usage.

Design and Pilot Evaluation of a Prototype Sensorized Trunk Exoskeleton

Trunk exoskeletons are wearable devices that support wearers during physically demanding tasks by reducing biomechanical loads and increasing stability. In this paper, we present a prototype sensorized passive trunk exoskeleton, which includes five motion processing units (3-axis accelerometers and gyroscopes with onboard digital processing), four one-axis flex sensors along the exoskeletal spinal column, and two one-axis force sensors for measuring the interaction force between the wearer and exoskeleton. A pilot evaluation of the exoskeleton was conducted with two wearers, who performed multiple everyday tasks (sitting on a chair and standing up, walking in a straight line, picking up a box with a straight back, picking up a box with a bent back, bending forward while standing, bending laterally while standing) while wearing the exoskeleton. Illustrative examples of the results are presented as graphs. Finally, potential applications of the sensorized exoskeleton as the basis for a semi-active exoskeleton design or for audio/haptic feedback to guide the wearer are discussed.

Toward Real-Time Detection of Object Lifting Using Wearable Inertial Measurement Units

Back injuries and other occupational injuries are common in workers who engage in long, arduous physical labor. The risk of these injuries could be reduced using assistive devices that automatically detect an object lifting motion and support the user while they perform the lift; however, such devices must be able to detect the lifting motion as it occurs. We thus developed a system to detect the start and end of a lift (performed as a stoop or squat) in real time based on pelvic angle and the distance between the user's hands and the user's center of mass. The measurements were input to an algorithm that first searches for hand-center distance peaks in a sliding window, then checks the pelvic displacement angle to verify lift occurrence. The approach was tested with 5 participants, who performed a total of 100 lifts of four different types. The times of actual lifts were determined by manual video annotation. The median time error (absolute difference between detected and actual occurrence time) for lifts that were not false negatives was 0.11 s; a lift was considered a false negative if it was not detected within two seconds of it actually occurring. Furthermore, 95% of lifts that were detected occurred within 0.28 s of actual occurrence. This shows that it is possible to reliably detect lifts in real time based on the pelvic displacement angle and the distance between the user's hands and their center of mass.

Evaluation of the HeroWear Apex back-assist exosuit during multiple brief tasks

Trunk exoskeletons are wearable devices that support humans during physically demanding tasks by reducing biomechanical loads on the back. While most trunk exoskeletons are rigid devices, more lightweight soft exoskeletons (exosuits) have recently been developed. One such exosuit is the HeroWear Apex, which achieved promising results in the developers' own work but has not been independently evaluated. This paper thus presents an evaluation of the Apex with 20 adult participants during multiple brief tasks: standing up from a stool with a symmetric or asymmetric load, lifting a unilateral or bilateral load from the floor to waist level, lifting the same bilateral load with a 90-degree turn to the right, lowering a bilateral load from waist level to floor, and walking while carrying a bilateral load. The tasks were performed in an ABA-style protocol: first with exosuit assistance disengaged, then with it engaged, then disengaged again. Four measurement types were taken: electromyography (of the erector spinae, rectus abdominis, and middle trapezius), trunk kinematics, self-report ratings, and heart rate. The exosuit decreased the erector spinae electromyogram by about 15% during object lifting and lowering tasks; furthermore, participants found the exosuit mildly to moderately helpful. No adverse effects on other muscles or during non-lifting tasks were noted, and a decrease in middle trapezius electromyogram was observed for one task. This confirms that the HeroWear Apex could reduce muscle demand and fatigue. The results may transfer to other exoskeletons with similar design principles, and may inform researchers working with other wearable devices.

Occupational exoskeletons: A roadmap toward large-scale adoption. Methodology and challenges of bringing exoskeletons to workplaces

The large-scale adoption of occupational exoskeletons (OEs) will only happen if clear evidence of effectiveness of the devices is available. Performing product-specific field validation studies would allow the stakeholders and decision-makers (e.g., employers, ergonomists, health, and safety departments) to assess OEs' effectiveness in their specific work contexts and with experienced workers, who could further provide useful insights on practical issues related to exoskeleton daily use. This paper reviews present-day scientific methods for assessing the effectiveness of OEs in laboratory and field studies, and presents the vision of the authors on a roadmap that could lead to large-scale adoption of this technology. The analysis of the state-of-the-art shows methodological differences between laboratory and field studies. While the former are more extensively reported in scientific papers, they exhibit limited generalizability of the findings to real-world scenarios. On the contrary, field studies are limited in sample sizes and frequently focused only on subjective metrics. We propose a roadmap to promote large-scale knowledge-based adoption of OEs. It details that the analysis of the costs and benefits of this technology should be communicated to all stakeholders to facilitate informed decision making, so that each stakeholder can develop their specific role regarding this innovation. Large-scale field studies can help identify and monitor the possible side-effects related to exoskeleton use in real work situations, as well as provide a comprehensive scientific knowledge base to support the revision of ergonomics risk-assessment methods, safety standards and regulations, and the definition of guidelines and practices for the selection and use of OEs.

Bilateral Asymmetry of Hand Force Production in Dynamic Physically-Coupled Tasks

Physically-coupled bimanual tasks (activities where a force effect occurs between two human limbs) involve the coordination and cooperation of bilateral arms. Such uncertain contribution of two arms is often studied under static configuration, which is not sufficient to typify all activities of daily life (ADLs). This study aims to investigate peoples bilateral force production and control in dynamic tasks. Experiments were conducted with a customized robotic system that is characterized with two handles and programmable force fields between them. Fourteen healthy right-handed human volunteers were instructed to generate force with each hand when performing predefined trajectory tracking tasks, in which the sum of forces contributed by the left and the right hand is required to equal a target force. Significant asymmetry was found in the force output between bilateral hands. With the homologous muscles activated synchronously, the contribution of the left hand was larger, while when the non-homogenous muscles were activated synchronously, the laterality was subject to the moving direction. In addition, when considering the force difference between two hands in terms of direction and magnitude, the former decreased with the increase of the target force, but the latter was more sensitive to moving directions. The results reveal the unique characteristics of non-isometric force control tasks compared with isometric ones.

Effects of industrial back-support exoskeletons on body loading and user experience: an updated systematic review

This study is an updated systematic review of papers published in the last 5 years on industrial back-support exoskeletons. The research questions were aimed at addressing the recent findings regarding objective (e.g. body loading, user performance) and subjective evaluations (e.g. user satisfaction), potential side effects, and methodological aspects of usability testing. Thirteen studies of active and twenty of passive exoskeletons were identified. The exoskeletons were tested during lifting and bending tasks, predominantly in laboratory settings and among healthy young men. In general, decreases in participants' back-muscle activity, peak L5/S1 moments and spinal compression forces were reported. User endurance during lifting and static bending improved, but performance declined during tasks that required increased agility. The overall user satisfaction was moderate. Some side effects were observed, including increased abdominal/lower-limb muscle activity and changes in joint angles. A need was identified for further field studies, involving industrial workers, and reflecting actual work situations. Practitioner summary: Due to increased research activity in the field, a systematic review was performed of recent studies on industrial back-support exoskeletons, addressing objective and subjective evaluations, side effects, and methodological aspects of usability testing. The results indicate the efficiency of exoskeletons in back-load reduction and a need for further studies in real work situations. Abbrevaitions: BB: biceps brachii; BF: biceps femoris; CoM: centre of mass; DA: deltoideus anterior; EMG: electromyography; ES: erector spinae; ES-C: erector spinae-cervical; ESI: erector spinae iliocostalis; ESI-L: erector spinae iliocostalis-lumborum; ESL: erector spinae longissimus; ES-L: erector spinae-lumbar; ESL-L: erector spinae longissimus-lumborum; ESL-T: erector spinae longissimus-thoracis; ES-T: erector spinae-thoracic; GM: glutaeus maximus; LBP: low back pain; LD: latissimus dorsi; LPD: local perceived discomfort scale; LPP: local perceived pressure scale; MS: multifidus spinae; MSD: musculoskeletal disorder; M-SFS: modified spinal function sort; NMV: no mean value provided; OA: obliquus abdominis (internus and externus); OEA: obliquus externus abdominis; OIA : obliquus internus abdominis; RA: rectus abdominis; RF: rectus femoris; RoM: range of motion; SUS: system usability scale; T: trapezius (pars Ascendens and Descendens); TA: trapezius pars ascendens; TC: mid-cervical trapezius; TD: trapezius pars descendens; VAS: visual analog scale; VL: vastus lateralis; VM: vastus medialis.

Load Position and Weight Classification during Carrying Gait Using Wearable Inertial and Electromyographic Sensors

Lifting and carrying heavy objects is a major aspect of physically intensive jobs. Wearable sensors have previously been used to classify different ways of picking up an object, but have seen only limited use for automatic classification of load position and weight while a person is walking and carrying an object. In this proof-of-concept study, we thus used wearable inertial and electromyographic sensors for offline classification of different load positions (frontal vs. unilateral vs. bilateral side loads) and weights during gait. Ten participants performed 19 different carrying trials each while wearing the sensors, and data from these trials were used to train and evaluate classification algorithms based on supervised machine learning. The algorithms differentiated between frontal and other loads (side/none) with an accuracy of 100%, between frontal vs. unilateral side load vs. bilateral side load with an accuracy of 96.1%, and between different load asymmetry levels with accuracies of 75-79%. While the study is limited by a lack of electromyographic sensors on the arms and a limited number of load positions/weights, it shows that wearable sensors can differentiate between different load positions and weights during gait with high accuracy. In the future, such approaches could be used to control assistive devices or for long-term worker monitoring in physically demanding occupations.

Characterizing Human Box-Lifting Behavior Using Wearable Inertial Motion Sensors

Although several studies have used wearable sensors to analyze human lifting, this has generally only been done in a limited manner. In this proof-of-concept study, we investigate multiple aspects of offline lift characterization using wearable inertial measurement sensors: detecting the start and end of the lift and classifying the vertical movement of the object, the posture used, the weight of the object, and the asymmetry involved. In addition, the lift duration, horizontal distance from the lifter to the object, the vertical displacement of the object, and the asymmetric angle are computed as lift parameters. Twenty-four healthy participants performed two repetitions of 30 different main lifts each while wearing a commercial inertial measurement system. The data from these trials were used to develop, train, and evaluate the lift characterization algorithms presented. The lift detection algorithm had a start time error of 0.10 s ± 0.21 s and an end time error of 0.36 s ± 0.27 s across all 1489 lift trials with no missed lifts. For posture, asymmetry, vertical movement, and weight, our classifiers achieved accuracies of 96.8%, 98.3%, 97.3%, and 64.2%, respectively, for automatically detected lifts. The vertical height and displacement estimates were, on average, within 25 cm of the reference values. The horizontal distances measured for some lifts were quite different than expected (up to 14.5 cm), but were very consistent. Estimated asymmetry angles were similarly precise. In the future, these proof-of-concept offline algorithms can be expanded and improved to work in real-time. This would enable their use in applications such as real-time health monitoring and feedback for assistive devices.