EMG-Assisted Algorithm to Account for Shoulder Muscles Co-Contraction in Overhead Manual Handling

Abstract

Glenohumeral stability is essential for a healthy function of the shoulder. It is ensured partly by the scapulohumeral muscular balance. Accordingly, modelling muscle interactions is a key factor in the understanding of occupational pathologies, and the development of ergonomic interventions. While static optimization is commonly used to estimate muscle activations, it tends to underestimate the role of shoulder’s antagonist muscles. The purpose of this study was to implement experimental electromyographic (EMG) data to predict muscle activations that could account for the stabilizing role of the shoulder muscles. Kinematics and EMG were recorded from 36 participants while lifting a box from hip to eye level. Muscle activations and glenohumeral joint reactions were estimated using an EMG-assisted algorithm and compared to those obtained using static optimization with a generic and calibrated model. Muscle activations predicted with the EMG-assisted method were generally larger. Additionally, more interactions between the different rotator cuff muscles, as well as between primer actuators and stabilizers, were predicted with the EMG-assisted method. Finally, glenohumeral forces calculated from a calibrated model remained within the boundaries of the glenoid stability cone. These findings suggest that EMG-assisted methods could account for scapulohumeral muscle co-contraction, and thus their contribution to the glenohumeral stability.

Targeted Achilles Tendon Training and Rehabilitation Using Personalized and Real-Time Multiscale Models of the Neuromusculoskeletal System

“…Despite the lack of direct validation of our results, the individual components of our modeling pipeline have been tested and validated (or verified) individually. Our rigid-body EMG-informed NMS model has been used in multiple applications, showing to produce physiologically plausible muscle forces across the lower and upper limbs (Hoang et al, 2018;Kian et al, 2019;Assila et al, 2020;Maniar et al, 2020). Additionally, the personalization via ultrasound and MRI measurements, the calibration of the neuromuscular parameters in the rigid body model, and the tuning of the material properties of the FE model, all contribute to generate physiologically plausible results.…”

A review of Multibody Dynamic versus Finite Element Analyses applied in palaeoanthropology: what can we expect for the study of hominin postcranial remains?

“…Palaeoanthropology would benefit from methodological advances in other fields such as human sport and medicine. In MDA, for example, some advances have been made in muscle force estimation by coupling in-vivo electromyographic data with the resolution of muscle redundancy equations (Vigouroux et al, 2007;Assila et al, 2020;Sarshari et al, 2020) or in joint stability compliance (Dickerson et al, 2007;Blache et al, 2017a;2017bAkhavanfar et al, 2019. Both aspects are crucial for an accurate solution of muscle redundancy issues and to compute muscle forces in humans, and, therefore, by extension, to apply it to the hominin fossil record (Blasi-Toccacceli et al, 2020).…”

Electromyography-Assisted Neuromusculoskeletal Models Can Estimate Physiological Muscle Activations and Joint Moments Across the Neck Before Impacts

“…During Stage 1 and 3 of the calibration process all activations were constrained to their mapped input signals. ies as SO works fairly well in gait, however, these issues were experienced at the shoulder [58], where contact forces were very variable. Also, those peaks usually disappeared after calibrating the model.…”