Musculoskeletal-Modeling-Based, Full-Body Load-Assessment Tool for Ergonomists (MATE): Method Development and Proof of Concept Case Studies.

A new ergonomic-risk-assessment tool was developed that combines musculoskeletal-model-based loading estimates with insights from fatigue failure theory to evaluate full-body musculoskeletal loading during dynamic tasks. Musculoskeletal-modeling output parameters, i.e., joint contact forces and muscle forces, were combined with tissue-specific injury thresholds that account for loading frequency to determine the injury risk for muscles, lower back, and hip cartilage. The potential of this new risk-assessment tool is demonstrated for defining ergonomic interventions in terms of lifting characteristics, back and shoulder exoskeleton assistance, box transferring, stoop lifting, and an overhead wiring task, respectively. The MATE identifies the risk of WMSDs in different anatomical regions during occupational tasks and allows for the evaluation of the impact of interventions that modify specific lifting characteristics, i.e., load weight versus task repetition. Furthermore, and in clear contrast to currently available ergonomic assessment scores, the effects of the exoskeleton assistance level on the risk of WMSDs of full-body musculoskeletal loading (in particular, the muscles, lower back, and hips) can be evaluated and shows small reductions in musculoskeletal loading but not in injury risk. Therefore, the MATE is a risk-assessment tool based on a full-body, musculoskeletal-modeling approach combined with insights from the fatigue failure theory that shows the proof of concept of a shoulder and back exoskeleton. Furthermore, it accounts for subject-specific characteristics (age and BMI), further enhancing individualized ergonomic-risk assessment.

The Exo4Work shoulder exoskeleton effectively reduces muscle and joint loading during simulated occupational tasks above shoulder height.

INTRODUCTION: Excessive physical shoulder musculoskeletal loading (muscle and joint contact forces), known to contribute to work-related shoulder disorders, can be reduced by a passive shoulder exoskeleton during quasi-static tasks. However, its effect on neighboring joints i.e. elbow, lower back, hip, and knee and its effect on joint contact forces have not been investigated. Furthermore, the effect of the exoskeleton's assistance versus movement adaptation when wearing the exoskeleton on musculoskeletal loading remains unexplored. METHODS: 3D motion capture and ground reaction forces were measured while 16 participants performed 5 simulated occupational tasks with and without the exoskeleton. A musculoskeletal modeling workflow was used to calculate musculoskeletal loading. Shoulder muscle fatigue was quantified using surface EMG. In addition, exoskeletons usability was quantified using the system usability scale. RESULTS: When wearing the passive shoulder exoskeleton, shoulder and elbow musculoskeletal loading decreased during the high lift and overhead wiring task, without increasing the musculoskeletal load at the back, hip and knee. In contrast, musculoskeletal loading in the shoulder, as well as in the knee increased while lifting a box from the ground to knee height and from elbow height to shoulder height. When wearing the exoskeleton, muscle activity of the Trapezius descendens, Deltoideus medius and Biceps brachii were reduced during the high lift. CONCLUSION: The passive shoulder exoskeleton reduces musculoskeletal loading in the lower back, shoulder and elbow during simulated occupational tasks above shoulder height. In contrast, for tasks below shoulder height, the use of the exoskeleton needs to be critically reviewed to avoid increased musculoskeletal loading also in neighboring joints due to altered movement execution when wearing the exoskeleton.

Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim.

Inertial capture (InCap) systems combined with musculoskeletal (MSK) models are an attractive option for monitoring 3D joint kinematics in an ecological context. However, the primary limiting factor is the sensor-to-segment calibration, which is crucial to estimate the body segment orientations. Walking, running, and stair ascent and descent trials were measured in eleven healthy subjects with the Xsens InCap system and the Vicon 3D motion capture (MoCap) system at a self-selected speed. A novel integrated method that combines previous sensor-to-segment calibration approaches was developed for use in a MSK model with three degree of freedom (DOF) hip and knee joints. The following were compared: RMSE, range of motion (ROM), peaks, and R2 between InCap kinematics estimated with different calibration methods and gold standard MoCap kinematics. The integrated method reduced the RSME for both the hip and the knee joints below 5°, and no statistically significant differences were found between MoCap and InCap kinematics. This was consistent across all the different analyzed movements. The developed method was integrated on an MSK model workflow, and it increased the sensor-to-segment calibration accuracy for an accurate estimate of 3D joint kinematics compared to MoCap, guaranteeing a clinical easy-to-use approach.