Assessing the Short-Term Effects of Dual Back-Support Exoskeleton within Logistics Operations

Abstract

Logistics activities involve significant risk factors for the development of work-related musculoskeletal disorders (WMSD), particularly low back pain. Exoskeletons have emerged as potential solutions to mitigate these risks. This study assesses the short-term effects of dual passive back-support exoskeletons (Auxivo and Htrius) on WMSD risk factors in logistics operations. Two workstations were evaluated using self-report ratings, postural assessment, and surface electromyography (EMG). The results indicate that both exoskeletons provided relief and support during tasks, with Htrius showing a slight advantage. Exoskeletons reduced perceived exertion, especially during trunk flexion tasks, and improved posture, particularly in tasks involving manual lifting loads at lower height levels. While variations in muscular activity were observed, the Htrius exoskeleton showed a trend of reducing lumbar muscle activity. Overall, Htrius demonstrated promise in improving workers’ comfort, safety, and efficiency, potentially reducing WMSD risk and muscular fatigue. However, individual preferences and workplace-specific characteristics should be considered when selecting exoskeleton models. Future research should explore the effects on different loads, genders, and EMG of different muscles to further enhance the understanding and application of exoskeletons in occupational contexts.

1. Introduction

Work-related musculoskeletal disorders (WMSD), particularly low back pain, represent a significant concern in workplaces, especially in the logistics industry [1]. Based on survey findings and accident records, it is reported that 41% of workers in the European Union experience low back pain [2]. The logistics sector is among the sectors reporting the highest rates of low back pain [2]. Repetitive tasks, force application, and awkward body postures are key factors in the development of these injuries, resulting in localized pain, a feeling of heaviness, and a loss of strength, among other symptoms [3,4].

Modern industry constantly seeks efficiency and process automation [5]. However, in the logistics sector, numerous workers continue to perform manual handling operations (MHO) [6], an activity recognized for its association with the development of WMSD [7]. MHO include holding, lifting, lowering, carrying, turning, pulling, or pushing loads with one or both hands, performed by one or more workers [8].

Assessing MHO is crucial for understanding the physical demands placed on workers and implementing solutions to mitigate the risk of injury. For this purpose, several validated methods for assessing the WMSD risk are available in the scientific literature. These methods have been categorized into three levels, namely the following: (1) self-report and checklists; (2) observational methods; and (3) direct measurement methods [9,10]. Several studies have applied these methods to assess the WMSD risk in MHO. For example, [11] applied the Borg Category Ratio-10 (CR-10) scale, a self-report method, [12] applied the Rapid Entire Body Assessment (REBA), an observational method, and [13] applied surface electromyography (EMG) and inertial measurement units, both direct measurement techniques. In these studies, although the application of each method individually fulfilled the evaluation purpose, their combined use was found to possibly allow for a more accurate assessment. Each method targets specific aspects of the work environment and task characteristics, enabling a detailed analysis of risk factors. By combining multiple assessment methods, a broader range of issues can be identified, leading to more effective prevention and mitigation strategies [14].

In dynamic logistics environments, full automation is not always feasible due to product variability and the need for quick human decisions [15]. Given this scenario, collaboration between humans and robots emerges as a promising solution. Exoskeletons, wearable external mechanical structures that increase the human’s physical capacity, stand out as an innovative technology in this context [16]. These devices, divided into active and passive, offer support to physical activities, with passive ones being particularly relevant for industrial environments [17]. Passive exoskeletons, which do not require external energy, can store and use the energy generated by human movements. These devices are designed to support manual work tasks, such as manual lifting loads, and they are already being tested in several companies and laboratory studies [15].

Several studies have proven the effectiveness of these technologies in reducing muscular activity and improving the body posture adopted by their users [18,19,20,21,22]. For instance, van Sluijis et al. [20] conducted a laboratory-based study (n = 30) utilizing the Auxivo exoskeleton to lift loads (6 kg to 20 kg). They observed reductions in lumbar muscle activity ranging from 6.83% to 14.23%. Testing the same exoskeleton (n = 20), within a simulated lifting task (15 kg), Arauz et al. [19] observed a decrease in flexion–extension movement ranges on the back joint through a kinematics analysis. Participants reported mostly positive experiences with the exoskeleton. In another study (n = 12) testing the Htrius exoskeleton, in two repetitions of lifting a load of 13 kg, a decrease of 20% in lumbar muscle activity and a decrease in trunk flexion were observed [21]. However, these studies were conducted within a laboratory setting, underscoring the necessity to validate such equipment in real work environments. The extant scientific literature underscores the efficacy of ergonomic interventions in mitigating the WMSD risk [23]. Therefore, an ergonomic intervention at a workstation entails the assessment of the conditions under which given work takes place [24].

In this context, this study aims to assess the impact of using dual passive back-support exoskeletons on WMSD risk factors in industrial settings within a logistics company, highlighting the crucial role of ergonomics in validating these devices for occupational use.

2. Materials and Methods

This study was conducted at the warehouse of a logistics company. The objective was to investigate the influence of dual exoskeletons on WMSD risk factors. To conduct this evaluation, two workstations were selected by the company’s managers (due to workers’ complaints), with each assigned to two picking methods, pick by store (PBS) and pick by line (PBL). For each workstation, a single worker was assigned. This was due to the individual working experience with only each picking method evaluated. This approach ensures the accuracy of the data collected, reflecting the participants’ expertise in the working methods and avoiding any confounding variables that could result from unfamiliarity with the tasks. Both workers signed an informed consent form, in agreement with the Committee of Ethics for Research in Social and Human Sciences of the University of Minho (approval number CEICSH 145/2023), respecting the Declaration of Helsinki and Portuguese Law of Personal Data Protection (Lei nº 67/98).

To avoid disrupting the normal company workflow, the ergonomic assessment considered task simulation in a real-world scenario, respecting the same conditions as the commonly performed tasks in each picking method.

2.1. Description of the Logistic Tasks

In the PBS, the evaluated task involved the manual handling of boxes weighing approximately 4 kg each, with the following measurements: 40 cm long, 28 cm wide, and 23 cm high. These boxes were initially placed on two pallets (whose surface was 15 cm from the ground) located to the left and right of the workstation, with a third pallet positioned centrally for box placement. The process entailed alternately picking a box from the left pallet and placing it on the central pallet, followed by picking a box from the right pallet and placing it on the central pallet. In the PBL scenario, the evaluated task involved transferring boxes, also weighing approximately 4 kg each, with the following measurements: 45 cm long, 29 cm wide, and 23 cm high. The boxes were transferred from a central pallet (whose surface was 30 cm from the ground) to two pallets (whose surfaces were 15 cm from the ground) situated on the left and right sides of the workstation. The process involved palletizing the boxes first onto the right-side pallet and then onto the left-side pallet. The tasks evaluated for both workstations are summarized in

Table 1. Description of PBS and PBL tasks.

Task	PBS	Base of the Box Height	PBL	Base of the Box Height
T1	Reach the box on level 7.	153 cm	Reach the box on level 5.	122 cm
T2	Reach the box on level 6.	130 cm	Reach the box on level 4.	99 cm
T3	Reach the box on level 5.	107 cm	Palletize box on proximal level 1.	15 cm
T4	Reach the box on level 3.	84 cm	Palletize box on proximal level 2.	38 cm
T5	Reach the box on level 2.	61 cm	Palletize box on distal level 1.	15 cm
T6	Reach the box on level 1.	38 cm	Palletize box on distal level 2.	38 cm
T7	Palletize box on level 1.	15 cm	Palletize box on distal level 3.	61 cm
T8	Palletize box on level 2.	38 cm	N.A.	N.A.
T9	Palletize box on level 3.	61 cm	N.A.	N.A.

.

Additionally, the setup for each workstation scenario is illustrated in Figure 1. In both workstations, the workers started from a free-standing posture. Given the nature of the MHO, all tasks required trunk and back movements, with box placement occurring at various height levels, as detailed in Table 1. Both participants were free to choose the movements they employed in palletizing the boxes (e.g., squatting or forward leaning), ensuring that the task was performed under realistic conditions.

2.2. Experimental Procedure

To assess the effects of two passive exoskeletons on WMSD risk factors, an experiment was designed applying three levels of musculoskeletal overload assessment techniques: (1) psychophysical evaluation through self-reported ratings; (2) postural assessment using the REBA method; and (3) direct measurement of muscle activity using EMG. Two passive exoskeletons designed to support the lumbar region during trunk flexion tasks were used, namely the Auxivo and Htrius exoskeletons (Figure 2). Auxivo is a passive exoskeleton designed to assist with lifting tasks, resembling a backpack. It weighs 0.9 kg, and it has shoulder straps, a chest strap, thigh sleeves, and a waist support strap. Two elastic bands stretch from the back section to the thigh sleeves, providing support when the user bends forward or crouches. Assistance is manually adjustable via shoulder loops, allowing users to regulate the level of support [19]. Htrius is also a passive exoskeleton developed to assist with lifting tasks. It is composed of a supportive back structure modeled after a human back, which is flexible and adjustable to human movements. It is attached to 2 shoulder straps and 2 tight straps on its middle position. Due to the springs attached to the back structure, the exoskeleton provides a slight spring action that supports the lumbar region, bringing the subject to an optical position. The equipment weighs 1.18 kg [21,25].

The selection of these two types of exoskeletons is justified by the company’s interest in testing these specific models. These exoskeletons are advertised for use within logistics tasks that involve the manual handling of load and forward lean postures, as indicated by their manufacturers [26,27]. Both exoskeletons were worn with the assistance of the researchers, according to the manufacturer’s guidelines and recommendations, to ensure a correct fit.

For the psychophysical assessment, a questionnaire was developed to assess the participants’ subjective perceptions. This questionnaire aimed to measure perceptions regarding the relief provided via the exoskeleton, the reduction in backloading, the range of motion, the ease of handling loads, the interference with the task, support in carrying out the tasks, and perceived exertion. Notably, the questionnaire incorporated established psychometric instruments, including the Likert scale [28] and Borg CR-10 [29], to ensure the robust measurement of participants’ responses. The Likert scale ranges from 1 to 5, and the Borg CR-10 Scale ranges from 1 to 10.

For the postural assessment, the REBA method [30] was applied. This method involves a systematic approach comprising several steps. Initially, the work area is examined to identify the tasks and postures involved. Subsequently, video recordings or photographs are captured of workers performing these tasks. The postures are then analyzed using established guidelines to assess the level of WSMD risk. For the application of the REBA method, the body analysis is segmented into two groups: Group A and Group B. Group A includes the trunk, neck, and legs, while Group B comprises the upper arms, lower arms, and wrists. These groups are evaluated based on the joint displacement of the body segment from the neutral posture. The scores for Group A and Group B were calculated separately. The load/force score was added to the Group A score, and the load grip score was added to the Group B score to obtain the final scores for each group. Score C was derived from Scores A and B. The final REBA score was obtained by adding Score C to the activity score. The final REBA score was categorized into five levels according to the degree of risk. The higher the final score, the greater the level of risk. For each task studied, two postures were considered.

EMG data were collected bilaterally from the erector spinal Iliocostalis (ESI), erector spinal longissimus (ESL), and rectus abdominis (RA) using a wireless 8-channel biosignal Plux HUB^® (PLUX Wireless Biosignals S.A, Lisbon, Portugal ) [31]. The rationale behind choosing these specific muscle groups stemmed from their functional significance during manual handling operations (MHO). Specifically, the erector spinal muscles were selected due to their role in trunk extension and stabilization [32], while the RA muscles were chosen for their involvement in stabilizing the lumbar spine [33]. Furthermore, this selection process was informed by prior investigations assessing the efficacy of exoskeletons in MHO [18,20,21]. The placement of electrodes was carried out according to the established Surface Electromyography for the Non-Invasive Assessment of Muscles (SENIAM) guidelines [34], with an inter-electrode distance of 20 mm. A reference electrode was placed on the C7 spinous process. The locations of the EMG electrodes are shown in Figure 3. Data collection was performed using an 8-channel biosignal device with a sampling frequency of 1000 Hz, 100 GX input impedance, 110 dB common rejection factor, and 16-bit analog collection channels. Before experiments were conducted on each subject, the maximum voluntary contraction (MVC) values for each muscle were obtained. The subjects were instructed to perform three-second contractions for each muscle, with three-second intervals of rest between contractions. Data were processed using the MATLAB R2023a^® software v9.14. The raw signals were amplified, filtered (high pass at 10 Hz and low pass at 450 Hz), rectified, and smoothed using the root mean square (RMS) digital algorithm. The EMG data (average values for each task) were normalized using the MVC.

For each workstation, three test conditions were defined to compare the use of exoskeletons, namely the following:

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Condition 1 refers to the control situation (without an exoskeleton);

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Condition 2 uses the Auxivo exoskeleton;

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Condition 3 uses the Htrius exoskeleton.

The questionnaire’s application occurred after the completion of experimental conditions 2 and 3, and it was conducted in the presence of the researchers to ensure that all questions were understood by the participants. REBA and EMG assessments were performed for all conditions.

For the psychophysical and EMG study, table organization was conducted using Microsoft Excel^® V16.84. In the postural assessment and sample characterization, the same software was utilized for descriptive statistics, with the mean employed as a measure of central tendency.

3. Results and Discussion

As previously mentioned, the sample considered in this study consists of two participants, each assigned to one of the workstations under analysis. Both participants had previous experience with the use of both exoskeletons. The PBS worker was a female, aged 26 years, with a weight of 80 kg and a height of 166 cm. The PBL worker was a male, aged 25 years, with a weight of 75 kg and a height of 186 cm. Figure 4 presents the questionnaire results, comparing the application of two exoskeletons, Auxivo and Htrius, across two picking methods, PBS and PBL. For Figure 4a. the Likert scale was considered, ranging from 1 (strongly disagree) to 5 (strongly agree). For Figure 4b, the Borg CR-10 Scale was considered, ranging from 0 (nothing at all) to 10 (extremely strong).

The findings from Figure 4 provide insights into the comparative effectiveness of the two exoskeletons. Overall, both exoskeletons demonstrated benefits in terms of relief, a reduction in backloading, and support in carrying out the tasks.

A prior investigation involving a different type of back-support exoskeleton, featuring rigid metal bars, yielded contrasting outcomes regarding task support [35]. This may suggest the efficacy of the exoskeletons examined in the present study, which exclusively utilize flexible bands. Interestingly, the participant using the PBL method reported better ratings for range of motion, ease of handling loads, and interference with the tasks, possibly indicating that the exoskeletons might be particularly advantageous in line picking tasks. These results are consistent with previous studies that have also demonstrated positive self-report ratings in terms of range of motion [20], ease of performing the task [19], and interference with the task [35].

In terms of specific exoskeleton performance, Auxivo showed consistently higher ratings compared to Htrius across most measures, particularly in providing relief and reducing backloading and support in carrying out the tasks. This is mostly in line with perceived exertion, having a better result for Auxivo when compared with Htrius, at least for one of the picking methods (PBL), suggesting a potential difference in the perceived baseline effort between the two exoskeletons. Note that, in both picking methods, the perceived exertion for both exoskeletons was lower than the perceived exertion when the same tasks were carried out without exoskeleton support.

The results also highlight potential areas for improvement, notably in the range of motion and interference with the task, at least for one of the picking methods (PBS). Another noteworthy aspect is the gender of the PBS subject, as the perceived ratings might be affected by the equipment’s fit not being adequately tailored to female anatomy. Findings from another study, suggest that the exoskeleton used did not accommodate the bodies of many female participants, potentially blurring the understanding of its effects on them [19].

Regarding the REBA assessment,

Table 2. REBA results for the three conditions considered: without an exoskeleton, exoskeleton Auxivo, and exoskeleton Htrius, for each workstation.

		Without Exoskeleton				Exoskeleton Auxivo				Exoskeleton Htrius
		A	B	REBA Score	Risk Level	A	B	REBA Score	Risk Level	A	B	REBA Score	Risk Level
PBS	T1	2.0	3.0	3.0	Low	2.0	3.0	3.0	Low	2.0	3.0	3.0	Low
	T2	1.0	3.0	2.0	Low	1.0	3.0	2.0	Low	3.0	4.0	4.0	Medium
	T3	2.0	3.0	3.0	Low	2.0	1.0	2.0	Low	2.0	1.0	2.0	Low
	T4	5.0	4.0	6.0	Medium	3.0	4.0	4.0	Medium	2.0	4.0	4.0	Medium
	T5	6.0	4.0	8.0	High	5.0	4.0	6.0	Medium	4.0	4.0	5.0	Medium
	T6	6.0	3.0	7.0	Medium	6.0	3.0	6.5	Medium	5.0	3.0	5.0	Medium
	T7	6.5	4.0	8.5	High	5.5	4.0	7.0	Medium	4.5	4.0	5.5	Medium
	T8	5.5	4.5	7.5	High	4.0	4.5	5.5	Medium	4.0	4.5	5.5	Medium
	T9	3.5	4.0	5.0	Medium	3.0	2.5	4.0	Medium	4.5	4.0	5.5	Medium
PBL	T1	2.0	2.0	2.5	Low	1.0	2.0	1.5	Low	1.5	1.0	1.5	Low
	T2	1.5	2.0	2.0	Low	1.5	3.0	2.5	Low	2.5	3.0	3.0	Low
	T3	7.0	4.0	9.0	High	5.5	4.0	7.0	Medium	4.0	4.0	5.0	Medium
	T4	6.0	4.0	8.0	High	4.0	4.0	5.0	Medium	3.0	4.0	4.5	Medium
	T5	6.0	4.0	8.0	High	5.0	4.0	6.0	Medium	5.0	4.5	6.5	Medium
	T6	5.0	4.0	6.0	Medium	4.5	4.0	5.5	Medium	4.0	4.0	5.0	Medium
	T7	4.5	4.0	5.5	Medium	4.0	4.0	5.0	Medium	3.5	4.0	4.5	Medium

REBA Group A (A); Reba Group B (B); bold denotes the higher REBA scores.

presents the results of the postural evaluation for the various tasks at the PBS and PBL workstations.

The results from the postural assessment denote that the use of exoskeletons generally improves the work posture in most of the tasks, especially those that involve trunk flexion (PBS_T5, 7 and 8; PBL_T3,4 and 5), thereby reducing the WMSD risk. For tasks involving reaching boxes at high levels of height (PBS_T1, 2, and 3; PBL_T1 and 2), no improvement was registered when exoskeletons were used. In some cases, such as PBS_T2, within the Htrius condition, the REBA revealed higher scores than the other two conditions. This may be explained by the posture of the upper limbs (as indicated by the scores of Group B for this task), for which the exoskeleton provides no support. In another scenario, while the WMSD risk remained unchanged between conditions, the REBA score was higher without exoskeleton use (PBS_T4 and 6; PBL_T6 and 7). Among exoskeletons, differences were observed in REBA scores across some tasks. Despite the consistent maintenance of WMSD risk levels across exoskeleton conditions, the scoring consistently demonstrates lower values in the Htrius exoskeleton condition. Despite previous studies having demonstrated the effectiveness of passive exoskeletons in improving lower back posture [19,21], the present study provides novel evidence in this matter. That is, in addition to aligning with previous studies, the current study also demonstrates a reduction in the WMSD risk using a posture-validating method for this purpose.

The muscle activity of the three tested conditions is shown in Figure 5. Muscle activity is presented in average RMS values corresponding to the percentage of muscle contraction throughout the tested task (expressed as % of MVC).

The findings for PBS (Figure 5a) indicate no substantial reduction in muscle activity when comparing the exoskeleton condition to the condition without exoskeletons, except for the R_RA muscle in the Auxivo exoskeleton condition, which exhibited a decrease of 6.6%. In PBL (Figure 5b), the results demonstrate notable reductions in muscle activity across conditions. The Auxivo exoskeleton condition, compared to the condition without an exoskeleton, showed a decrease in R_ESL muscle activity by 22.5%. Likewise, for the Htrius exoskeleton condition, compared to the condition without an exoskeleton, reductions of 4.1% in R_ESI, 12.0% in R_ESL, 9.4% in R_RA, and 11.5% in L_RA, were observed.

The decrease in back erector muscle activity observed in PBL aligns with prior research findings [18,19,20,21]. However, the current study reveals a predominantly unilateral reduction, particularly on the right side of the body. Given that this study was conducted in a real workplace setting, allowing participants to perform tested activities freely without constraints imposed by any load manipulation techniques, it may account for the observed discrepancies between the right and left sides of the body. This holds significance since alterations in lifting posture have the potential to impact spinal loading within the lumbar region [36]. This phenomenon may necessitate further investigation within similar occupational environments. Regarding PBS, the outcomes are consistent with the self-rating assessment, further indicating that such equipment may not adequately fit the female anatomy, as previously demonstrated by Arauz et al. [19].

In summary, despite the self-reported worker preference favoring the Auxivo exoskeleton, the results of postural evaluation and muscular activity reveal that the Htrius exoskeleton proves to be a more promising tool for improving the safety and efficiency of workers in industrial environments, reducing the WMSD risk and, eventually, muscular fatigue. However, it is important to consider workers’ individual preferences and the specificities of each work environment when selecting the most suitable exoskeleton model. These results can provide valuable insights for the future development of support technologies and workplace injury prevention programs.

The main limitation of this study lies in the small sample size, the anthropometric differences between the subjects, and the use of the same load across tasks. Generalizing the results would require further careful evaluation, including a larger number of participants. Future studies may include an investigation of the effects of exoskeletons on load manipulations with different weights and exploring the differential impacts of exoskeletons based on the gender and anthropometric characteristics of the users. It may also be appropriate to assess the muscular activity of other lumbar muscles and antagonistic muscles (to verify whether the use of exoskeletons does not generate compensatory effects in participants) and apply direct measurement techniques to evaluate postures.

4. Conclusions

In conclusion, the results obtained in this study provide a short-term analysis of the influence of exoskeletons in a real-world context within a logistics company. It was observed that, overall, the use of exoskeletons had a positive impact on various evaluated metrics, including psychophysical assessment, postural evaluation, and muscular activity assessment.

In the psychophysical analysis, the findings of the subjective assessment suggest that both Auxivo and Htrius exoskeletons offer significant benefits in terms of relief and support during picking tasks, with Auxivo showing a slight edge in performance across various metrics. Regarding perceived exertion, the exoskeletons demonstrated a reduction in the perceived effort compared to performing tasks without support, especially in activities involving trunk flexion, as evidenced by the results of the postural assessment. Furthermore, the exoskeletons were effective in improving the workers’ posture, reducing the WMSD risk, particularly in tasks requiring load manipulation at lower height levels (involving trunk flexion). Regarding muscular activity, although some variations were observed between exoskeleton models and test conditions, the results suggest a general trend of reducing the muscular activity of the lumbar muscles with the use of the Htrius exoskeleton, which may indicate a decrease in the physical effort required during task execution.