Simulating the effect of glenohumeral capsulorrhaphy on kinematics and muscle function

Scapular morphology variation affects reverse total shoulder arthroplasty biomechanics. A predictive simulation study using statistical and musculoskeletal shoulder models

Reverse total shoulder arthroplasty (RTSA) accounts for over half of shoulder replacement surgeries. At present, the optimal position of RTSA components is unknown. Previous biomechanical studies have investigated the effect of construct placement to quantify mobility, stability and functionality postoperatively. While studies have provided valuable information on construct design and surgical placement, they have not systematically evaluated the importance of scapular morphology on biomechanical outcomes. The aim of this study was to assess the influence of scapular morphology variation on RTSA biomechanics using statistical models, musculoskeletal modeling and predictive simulation. The scapular geometry of a musculoskeletal model was altered across six modes of variation at four levels (±1 and ±3 SD) from a clinically derived statistical shape model. For each model, a standardized virtual surgery was performed to place RTSA components in the same relative position on each model then implemented in 50 predictive simulations of upward and lateral reaching tasks. Results showed morphology affected functional changes in the deltoid moment arms and recruitment for the two tasks. Variation of the anatomy that reduced the efficiency of the deltoids showed increased levels of muscle force production, joint load magnitude and shear. These findings suggest that scapular morphology plays an important role in postoperative biomechanical function of the shoulder with an implanted RTSA. Furthermore a "one-size-fits-all" approach for construct surgical placement may lead to suboptimal patient outcomes across a clinical population. Patient glenoid as well as scapular anatomy may need to be carefully considered when planning RTSA to optimize postoperative success.

Computational performance of musculoskeletal simulation in OpenSim Moco using parallel computing

Optimal control musculoskeletal simulation is a valuable approach for studying fundamental and clinical aspects of human movement. However, the high computational demand has long presented a substantial challenge, creating a need to improve simulation performance. The OpenSim Moco software package permits musculoskeletal simulation problems to be solved in parallel on multicore processors using the CasADi optimal control library, potentially reducing the computational demand. However, the computational performance of this framework has not been thoroughly examined. Thus, we aimed to investigate the computational speed-up obtained via multicore parallel computing relative to solving problems serially (i.e., using a single core) in optimal control simulations of human movement in OpenSim Moco. Simulations were solved using up to 18 cores with a variety of temporal mesh interval densities and using two different initial guess strategies. We examined a range of musculoskeletal models and movements that included two- and three-dimensional models, tracking and predictive simulations, and walking and reaching tasks. The maximum overall parallel speed-up was problem specific and ranged from 1.7 to 7.7 times faster than serial, with most of the speed-up achieved by about 6 processor cores. Parallel speed-up was generally greater on finer temporal meshes, while the initial guess strategy had minimal impact on speed-up. Considerable speed-up can be achieved for some optimal control simulation problems in OpenSim Moco by leveraging the multicore processors often available in modern computers. However, since improvements are problem specific, achieving optimal computational performance will require some degree of exploration by the end user.

Biomimetic Approaches for Human Arm Motion Generation: Literature Review and Future Directions

In recent years, numerous studies have been conducted to analyze how humans subconsciously optimize various performance criteria while performing a particular task, which has led to the development of robots that are capable of performing tasks with a similar level of efficiency as humans. The complexity of the human body has led researchers to create a framework for robot motion planning to recreate those motions in robotic systems using various redundancy resolution methods. This study conducts a thorough analysis of the relevant literature to provide a detailed exploration of the different redundancy resolution methodologies used in motion generation for mimicking human motion. The studies are investigated and categorized according to the study methodology and various redundancy resolution methods. An examination of the literature revealed a strong trend toward formulating intrinsic strategies that govern human movement through machine learning and artificial intelligence. Subsequently, the paper critically evaluates the existing approaches and highlights their limitations. It also identifies the potential research areas that hold promise for future investigations.

Be Careful What You Wish for: Cost Function Sensitivity in Predictive Simulations for Assistive Device Design

Software packages that use optimization to predict the motion of dynamic systems are powerful tools for studying human movement. These “predictive simulations” are gaining popularity in parameter optimization studies for designing assistive devices such as exoskeletons. The cost function is a critical component of the optimization problem and can dramatically affect the solution. Many cost functions have been proposed that are biologically inspired and that produce reasonable solutions, but which may lead to different conclusions in some contexts. We used OpenSim Moco to generate predictive simulations of human walking using several cost functions, each of which produced a reasonable trajectory of the human model. We then augmented the model with motors that generated hip flexion, knee flexion, or ankle plantarflexion torques, and repeated the predictive simulations to determine the optimal motor torques. The model was assumed to be planar and bilaterally symmetric to reduce computation time. Peak torques varied from 41.3 to 79.0 N·m for the hip flexion motors, from 48.0 to 94.2 N·m for the knee flexion motors, and from 42.6 to 79.8 N·m for the ankle plantarflexion motors, which could have important design consequences. This study highlights the importance of evaluating the robustness of results from predictive simulations.

The effects of operating height and the passage of time on the end-point performance of fine manipulative tasks that require high accuracy

Sustained shoulder abduction, which results from an inappropriate worktable height or tool shape and long task hours, leads to an accumulation of muscle fatigue and subsequent work-related injuries in workers. It can be alleviated by controlling the table height or ergonomic tool design, but workers who are doing some types of work that require a discomfortable posture, such as minimally invasive surgery, cannot avoid these situations. Loads to the shoulder joint or muscles result in several problems, such as muscle fatigue, deterioration of proprioception or changing movement strategies of the central nervous system, and these are critical to work that requires a high accuracy of the upper extremities. Therefore, in this paper, we designed and conducted an experiment with human participants to discuss how an inappropriate height of the work-table affects the task performance of workers who are performing a fine manipulative task that requires high accuracy of the end point. We developed an apparatus that can control the height and has four touch screens to evaluate the end-point accuracy with two different heights. Eighteen adults (9 women and 9 men) participated in the experiments, and the electromyography of their shoulder muscles, their movement stability, and task performance were measured for the analysis. We found that inappropriate height of a table brings about muscle fatigue, and time elapsed for conducting tasks accelerated the phenomenon. Task performance deteriorated according to increased fatigue, and improved movement stability is not enough to compensate for these situations.