Sensitivity of Neuromechanical Predictions to Choice of Glenohumeral Stability Modeling Approach

2020 ◽  
Vol 36 (4) ◽  
pp. 249-258
Author(s):  
Daniel C. McFarland ◽  
Alexander G. Brynildsen ◽  
Katherine R. Saul

Most upper-extremity musculoskeletal models represent the glenohumeral joint with an inherently stable ball-and-socket, but the physiological joint requires active muscle coordination for stability. The authors evaluated sensitivity of common predicted outcomes (instability, net glenohumeral reaction force, and rotator cuff activations) to different implementations of active stabilizing mechanisms (constraining net joint reaction direction and incorporating normalized surface electromyography [EMG]). Both EMG and reaction force constraints successfully reduced joint instability. For flexion, incorporating any normalized surface EMG data reduced predicted instability by 54.8%, whereas incorporating any force constraint reduced predicted instability by 43.1%. Other outcomes were sensitive to EMG constraints, but not to force constraints. For flexion, incorporating normalized surface EMG data increased predicted magnitudes of joint reaction force and rotator cuff activations by 28.7% and 88.4%, respectively. Force constraints had no influence on these predicted outcomes for all tasks evaluated. More restrictive EMG constraints also tended to overconstrain the model, making it challenging to accurately track input kinematics. Therefore, force constraints may be a more robust choice when representing stability.

Author(s):  
Basil Mathai ◽  
Sanjay Gupta

Musculoskeletal loading plays an important role in pre-clinical evaluations of hip implants, in particular, bone ingrowth and bone remodelling. Joint force estimation using musculoskeletal models evolved as a viable alternative to in vivo measurement owing to the development of computational resources. This study investigated the efficiencies of four eminent open-source musculoskeletal models in order to determine the model that predicts the most accurate values of hip joint reaction and muscle forces during daily activities. Seven daily living activities of slow walking, normal walking, fast walking, sitting down, standing up, stair down and stair up were simulated in OpenSim using inverse dynamics method. Model predictions of joint kinematics, kinetics and muscle activation patterns were compared with published results. The estimated values of hip joint reaction force were found to corroborate well with in vivo measurements for each activity. Although the estimated values of hip joint reaction force were within a satisfactory range, overestimation of hip joint reaction force (75% BW of measured value) was observed during the late stance phase of walking cycles for all the models. In case of stair up, stair down, standing up and sitting down activities, the error in estimated values of hip joint reaction force were within ~20% BW of the measured value. Based on the results of our study, the London Lower Extremity Model predicted the most accurate value of hip joint reaction force and therefore can be used for applied musculoskeletal loading conditions for numerical investigations on hip implants.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ehsan Sarshari ◽  
Yasmine Boulanaache ◽  
Alexandre Terrier ◽  
Alain Farron ◽  
Philippe Mullhaupt ◽  
...  

AbstractThere still remains a barrier ahead of widespread clinical applications of upper extremity musculoskeletal models. This study is a step toward lifting this barrier for a shoulder musculoskeletal model by enhancing its realism and facilitating its applications. To this end, two main improvements are considered. First, the elbow and the muscle groups spanning the elbow are included in the model. Second, scaling routines are developed that scale model’s bone segment inertial properties, skeletal morphologies, and muscles architectures according to a specific subject. The model is also presented as a Matlab toolbox with a graphical user interface to exempt its users from further programming. We evaluated effects of anthropometric parameters, including subject’s gender, height, weight, glenoid inclination, and degenerations of rotator cuff muscles on the glenohumeral joint reaction force (JRF) predictions. An arm abduction motion in the scapula plane is simulated while each of the parameters is independently varied. The results indeed illustrate the effect of anthropometric parameters and provide JRF predictions with less than 13% difference compared to in vivo studies. The developed Matlab toolbox could be populated with pre/post operative patients of total shoulder arthroplasty to answer clinical questions regarding treatments of glenohumeral joint osteoarthritis.


2020 ◽  
Vol 52 (7S) ◽  
pp. 260-260
Author(s):  
Hiroshi Sagawa ◽  
Michael R. Torry ◽  
Adam E. Jagodinsky ◽  
Sean Higinbotham ◽  
Michelle Sabick

Physiotherapy ◽  
2015 ◽  
Vol 101 ◽  
pp. e764
Author(s):  
R. Kiyama ◽  
H. Kakoi ◽  
T. Nojima ◽  
I. Kisanuki ◽  
T. Yamano ◽  
...  

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