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OCCUPATIONAL APPLICATIONSGlobalization and eCommerce continue to fuel unprecedented growth in the logistics and warehousing markets. Simultaneously, the biggest bottleneck for these industries is their human capital. Where automation and robotic solutions fail to deliver a return on investment, humans frequently take over handling tasks that place harmful loads and strains on the body. Occupational exoskeletons can reduce fatigue and strain by supporting the lower spine and are designed to prevent work-related musculoskeletal disorders and other injuries. They are a mid- to long-term investment for industries to improve ergonomic conditions in workplaces, with the potential for reducing absences from work, sick days logged, and workers compensation claims. To examine the effectiveness of the newly introduced Paexo Back exoskeleton, a study was completed with 10 participants who completed manual load handling tasks with and without the exoskeleton. Key findings include significant reductions in metabolic effort and low back loading when the exoskeleton is worn.

TECHNICAL ABSTRACTBackground: Work-related low back pain is a major threat to workers and society. Some new commercial and prototype exoskeletons are designed to specifically control the development of such disorders. Some beneficial effects of these exoskeletons have been reported earlier. Purpose: Determine the potential benefits of a newly introduced exoskeleton, Paexo Back, which is designed to reduce low back loading during lifting tasks. Methods: Ten healthy subjects participated in this study. To replicate a typical workplace situation, a repetitive lifting task with and without the exoskeleton was performed. For 5-min periods, the participants repeatedly lifted a 10-kg box from the floor onto a table and then placed it back on the floor. Effects of exoskeleton use were assessed using a diverse set of outcomes. Oxygen uptake and heart rate were measured using a wireless spiroergometry system. Activation levels of back, abdominal, and thigh muscles were also measured using a wireless electromyographic system. Kinematic data were recorded using an optoelectronic device, and ground reaction forces were measured with two force plates. Joint compression forces in the lower spine (L4/L5 and L5/S1) were estimated using the AnyBody™ Modeling System during the upward lifting portion of the lifting task (bringing the box to the table). Results: Using the exoskeleton resulted in significant reductions in oxygen rate (9%), activation of the back and thigh muscles (up to 18%), and peak and mean compression forces at L4/L5 (21%) and L5/S1 (20%). Conclusions: These results show that using the tested exoskeleton for a lifting task contributes to an increased metabolic efficiency, a reduction in the back muscle activation required to conduct the task, and a reduction in low back loading.

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Musculoskeletal models have traditionally relied on measurements of segment kinematics and ground reaction forces and moments (GRF&Ms) from marked-based motion capture and floor-mounted force plates, which are typically limited to laboratory settings. Recent advances in inertial motion capture (IMC) as well as methods for predicting GRF&Ms have enabled the acquisition of these input data in the field. Therefore, this study evaluated the concurrent validity of a novel methodology for estimating the dynamic loading of the lumbar spine during manual materials handling based on a musculoskeletal model driven exclusively using IMC data and predicted GRF&Ms. Trunk kinematics, GRF&Ms, L4-L5 joint reaction forces (JRFs) and erector spinae muscle forces from 13 subjects performing various lifting and transferring tasks were compared to a model driven by simultaneously recorded skin-marker trajectories and force plate data. Moderate to excellent correlations and relatively low magnitude differences were found for the L4-L5 axial compression, erector spinae muscle and vertical ground reaction forces during symmetrical and asymmetrical lifting, but discrepancies were also identified between the models, particularly for the trunk kinematics and L4-L5 shear forces. Based on these results, the presented methodology can be applied for estimating the relative L4-L5 axial compression forces under dynamic conditions during manual materials handling in the field.

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Low-back disorder risk can be modulated by pelvis-thorax coordination when lifting. To objectively discriminate between coordination patterns during lifting, the analytical methods used require evaluation. The primary study objective was to determine if continuous relative phase (CRP) and vector coding (VC) analyses can discriminate between lifting techniques that differ based on biomechanical risk criteria. The secondary objective was to determine if normalization/transformation of input segmental angular position and velocity data is required to discriminate between lifting techniques. Sixteen volunteers performed a sagittal lifting task using freestyle (FRE), flexed spine (FLX), and neutral spine (NTL) techniques. CRP and VC analyses were implemented to quantify pelvis-thorax coordination patterns based on time-normalized, phase-normalized, and Hilbert-transformed segmental angular kinematic data. Mean relative phase angles along with thorax-only and in-phase coupling patterns were significantly different between FRE-NTL and FLX-NTL techniques (p < 0.01), but not FRE-FLX (p > 0.44). This finding was consistent across all relative phase normalization/transformation methods. Therefore, CRP and VC analyses successfully discriminated between different lifting techniques, regardless of the relative phase normalization/transformation method used.

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Inertial motion capture (IMC) systems have become increasingly popular for ambulatory movement analysis. However, few studies have attempted to use these measurement techniques to estimate kinetic variables, such as joint moments and ground reaction forces (GRFs). Therefore, we investigated the performance of a full-body ambulatory IMC system in estimating 3D L5/S1 moments and GRFs during symmetric, asymmetric and fast trunk bending, performed by nine male participants. Using an ambulatory IMC system (Xsens/MVN), L5/S1 moments were estimated based on the upper-body segment kinematics using a top-down inverse dynamics analysis, and GRFs were estimated based on full-body segment accelerations. As a reference, a laboratory measurement system was utilized: GRFs were measured with Kistler force plates (FPs), and L5/S1 moments were calculated using a bottom-up inverse dynamics model based on FP data and lower-body kinematics measured with an optical motion capture system (OMC). Correspondence between the OMC+FP and IMC systems was quantified by calculating root-mean-square errors (RMSerrors) of moment/force time series and the interclass correlation (ICC) of the absolute peak moments/forces. Averaged over subjects, L5/S1 moment RMSerrors remained below 10Nm (about 5% of the peak extension moment) and 3D GRF RMSerrors remained below 20N (about 2% of the peak vertical force). ICCs were high for the peak L5/S1 extension moment (0.971) and vertical GRF (0.998). Due to lower amplitudes, smaller ICCs were found for the peak asymmetric L5/S1 moments (0.690-0.781) and horizontal GRFs (0.559-0.948). In conclusion, close correspondence was found between the ambulatory IMC-based and laboratory-based estimates of back load.

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