The findings suggest that passive back-support exoskeletons can contribute to improved spinal posture during manual palletizing and supports the role of motion capture as an objective assessment tool in ergonomic exoskeleton research.
Abstract
Background/Objectives: Musculoskeletal disorders of the lower back remain one of the leading causes of work-related health problems in occupations involving manual material handling. Passive industrial exoskeletons have gained increasing attention as a workplace-oriented assistance technology to reduce physical strain during lifting, carrying, and forward-bending tasks. This pilot study investigates the effect of a passive back-support exoskeleton on spinal posture during a simulated palletizing task. Manual palletizing remains relevant in manufacturing and distribution environments, despite increasing automation, because flexible, variable, and economically feasible work processes are still required. Methods: Five participants performed repeated palletizing cycles under three conditions: wearing an activated exoskeleton, wearing a deactivated exoskeleton, and without an exoskeleton. Spinal posture was captured using an optical motion-capture system with reflective markers placed along the spine. Marker-defined dorsal segment angles were calculated, normalized to an individual upright reference posture, and analyzed for deviations during distinct task phases. Results: The results indicate a tendency toward reduced spinal flexion when the exoskeleton was activated, particularly in the thoracic and lumbar regions. In contrast, larger deviations from the physiological reference posture were observed when the exoskeleton was deactivated or not worn. Inter-individual differences related to body height and prior ergonomic training were identified. Conclusions: Although the limited sample size does not allow definitive conclusions, the findings suggest that passive back-support exoskeletons can contribute to improved spinal posture during manual palletizing. The study provides a quantitative methodological framework for future large-scale investigations and supports the role of motion capture as an objective assessment tool in ergonomic exoskeleton research.
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