Skill Learning While Using Exoskeletons for Manual Materials Handling Operations in Warehouses and Distribution Centers

Abstract

Manual materials handling work is a significant contributor to musculoskeletal injuries, particularly in the warehousing and storage sector. This dissertation aimed to study how people learn to use passive exoskeletons for manual materials handling tasks, similar to those performed in warehouses and distribution centers. The goal was to provide the data needed to allow workers and their organizations considering exoskeleton implementation to have reasonable expectations regarding the temporality of the learning process, and possibly provide insights regarding how to better temporally organize training sessions to facilitate the motor learning process and the adoption of passive exoskeletons. If adopted, various studies, including the present one, suggested that exoskeletons have the potential to reduce the injury rates in warehouse product selection jobs (Alemi et al., 2019; Baltrusch et al., 2020; Bosch et al., 2016; Qu et al., 2021; Wei et al., 2020).

The current study assessed learning by measuring the changes in skill during retention and transfer conditions and comparing it to practice sets. The dependent variables for biomechanical performance were derived from the surface electromyographic (EMG) signals, trunk kinematic measures, and task durations. The current study had four main independent variables: exoskeleton conditions (with back-support passive exoskeleton vs. without), distributed practice methods, eight pick-to-placement height combinations, and four session types. Participants also reported their perceived level of effort, fatigue, and discomfort.

In this research study, a total of 36 participants were recruited. The participants practiced in simulated picking tasks, which involved the transfer of twelve 10 kg boxes to the destination pallet and subsequently returning these boxes to the source pallet at four different height levels.

The results showed that wearing the back-support passive exoskeleton significantly reduced muscle activity in the back muscles when lifting boxes, without increasing the load on shoulder or abdominal muscles.

The results showed that participants in the unassisted control group were able to learn the palletizing task after practicing 12 lifts at each pick-to-placement height condition during session 1. The exoskeleton-assisted group practiced the task without the exoskeleton in session 1 and then with the exoskeleton in session 2. This was enough for them to learn the task and adapt their muscles and postures to the various pick-to-placement heights. When the participants were under time pressure during the transfer, both the unassisted and exoskeleton-assisted groups had similar task durations; however, the back EMG activity was significantly lower for those using the exoskeleton.

While there were no significant differences between the multiple short-breaks and the single long-break schedules in terms of EMG muscle activity, kinematic measures, and task duration across most pick-to-placement height conditions, both groups showed improvement in performance over the course of the training and retention sessions.

In addition, the study found that participants did not show differences in EMG and kinematics trends, as assessed via calculated slopes, across the different pick-to-placement height conditions, regardless of exoskeleton conditions. This suggests that improvements in performance were not limited to specific conditions, emphasizing the value of variable practice and hybrid schedules.

In terms of subjective responses, the findings indicated that individuals using the exoskeleton generally experienced less fatigue; however, there was no significant difference in effort between exoskeleton users and non-users. It should be noted that several female users of exoskeletons reported hip discomfort while standing and chest discomfort during lifting tasks under time pressure.

Overall, these findings provide value for implementing exoskeleton technology, and suggest potential training protocols that would be effective for its use in manual material handling tasks.