The complexity of the human shoulder girdle enables the large mobility of the upper extremity, but also introduces instability of the glenohumeral (GH) joint. Shoulder movements are generated by coordinating large superficial and deeper stabilizing muscles spanning numerous degrees-of-freedom. How shoulder muscles are coordinated to stabilize the movement of the GH joint remains widely unknown. Musculoskeletal simulations are powerful tools to gain insights into the actions of individual muscles and particularly of those that are difficult to measure. In this study, we analyze how enforcement of GH joint stability in a musculoskeletal model affects the estimates of individual muscle activity during shoulder movements. To estimate both muscle activity and GH stability from recorded shoulder movements, we developed a Rapid Muscle Redundancy (RMR) solver to include constraints on joint reaction forces (JRFs) from a musculoskeletal model. The RMR solver yields muscle activations and joint forces by minimizing the weighted sum of squared-activations, while matching experimental motion. We implemented three new features: first, computed muscle forces include active and passive fiber contributions; second, muscle activation rates are enforced to be physiological, and third, JRFs are efficiently formulated as linear functions of activations. Muscle activity from the RMR solver without GH stability was not different from the computed muscle control (CMC) algorithm and electromyography of superficial muscles. The efficiency of the solver enabled us to test over 3600 trials sampled within the uncertainty of the experimental movements to test the differences in muscle activity with and without GH joint stability enforced. We found that enforcing GH stability significantly increases the estimated activity of the rotator cuff muscles but not of most superficial muscles. Therefore, a comparison of shoulder model muscle activity to EMG measurements of superficial muscles alone is insufficient to validate the activity of rotator cuff muscles estimated from musculoskeletal models.

This paper presents a trajectory optimization approach to the motion generation problem of hybrid locomotion strategies for a wheeled-legged quadrupedal robot with steerable wheels. To this end, traditional Single Rigid Body Dynamics has been employed and extended by adding a unicycle model for each leg, conveniently incorporating the nonholonomic rolling constraints. The proposed approach can generate hybrid locomotion strategies as well as pure driving and legged locomotion with minimum effort for the user. The effectiveness of the proposed approach has been experimentally validated on the humanoid quadruped CENTAURO, employing a hierarchical inverse kinematics engine to track the planned motions.

The complexity of the human shoulder girdle enables the large mobility of the upper extremity, but also introduces instability of the glenohumeral (GH) joint. Shoulder movements are generated by coordinating large superficial and deeper stabilizing muscles spanning numerous degrees-of-freedom. How shoulder muscles are coordinated to stabilize the movement of the GH joint remains widely unknown. Musculoskeletal simulations are powerful tools to gain insights into the actions of individual muscles and particularly of those that are difficult to measure. In this study, we analyze how enforcement of GH joint stability in a musculoskeletal model affects the estimates of individual muscle activity during shoulder movements. To estimate both muscle activity and GH stability from recorded shoulder movements, we developed a Rapid Muscle Redundancy (RMR) solver to include constraints on joint reaction forces (JRFs) from a musculoskeletal model. The RMR solver yields muscle activations and joint forces by minimizing the weighted sum of squared-activations, while matching experimental motion. We implemented three new features: first, computed muscle forces include active and passive fiber contributions; second, muscle activation rates are enforced to be physiological, and third, JRFs are efficiently formulated as linear functions of activations. Muscle activity from the RMR solver without GH stability was not different from the computed muscle control (CMC) algorithm and electromyography of superficial muscles. The efficiency of the solver enabled us to test 3600 trials sampled within the uncertainty of the experimental movements to test the differences in muscle activity with and without GH joint stability enforced. We found that enforcing GH stability significantly increases the estimated activity of the rotator cuff muscles but not of most superficial muscles. Therefore, a comparison of shoulder model muscle activity to EMG measurements of superficial muscles alone is insufficient to validate the activity of rotator cuff muscles estimated from musculoskeletal models.

This paper proposes a novel method to reliably calibrate a pair of sensorized insoles utilizing an array of capacitive tactile pixels (taxels). A new calibration setup is introduced that is scalable and suitable for multiple kinds of wearable sensors and a procedure for the simultaneous calibration of each of the sensors in the insoles is presented. The calibration relies on a two-step optimization algorithm that, firstly, enables determination of a relevant set of mathematical models based on the instantaneous measurement of the taxels alone, and, then, expands these models to include the relevant portion of the time history of the system. By comparing the resulting models with our previous work on the same hardware, we demonstrate the effectiveness of the novel method both in terms of increased ability to cope with the non-linear characteristics of the sensors and increased pressure ranges achieved during the experiments performed.

Common optimization approaches to solve the muscle redundancy problem in musculoskeletal simulations can predict shoulder contact forces that violate joint stability with lines of action outside the glenohumeral joint border. Approaches with simple joint stability constraints were previously introduced imposing an upper limit on the direction of the contact force to stay within a specified stability perimeter. Such approaches predicted higher rotator cuff muscle activation than without constraints, but the estimated joint contact forces were oriented along the specified perimeter, raising questions about validity. In this study, several glenohumeral stability formulations were investigated, and tested against in vivo measurements of glenohumeral contact forces from the Orthoload dataset on one participant data in three dumbbell tasks: lateral raise, posterior raise, and and anterior raise. The investigated formulations either imposed inequality constraints on the contact force direction to remain within a stability perimeter whose shape was varied, or added a penalty term as a criterion measure to the objective function that made the objective function costly for contact force directions to deviate from the glenoid cavity center. All stability formulations predicted contact force magnitudes that agreed relatively well to the in vivo measured forces except for the strictest formulation that constrained the joint contact force to be directed at the glenoid cavity center. Models that restricted the force direction to lie within a specified shape estimated force vectors that largely lay along the perimeters. Models that instead penalized force directions that deviated from the glenoid cavity center estimated relatively more accurate contact force directions within the glenoid cavity, though still not entirely in agreement with in vivo measurements. Our findings support the proposed penalty formulations as more reasonable and accurate than other investigated existing glenohumeral stability formulations. Author summary: In musculoskeletal models, the glenohumeral joint is often simplified as a purely rotational joint with no translation, whereas the actual joint movement involves both rotation and some translation, requiring stabilizing forces to prevent dislocation. Models that compute muscle forces based on a minimal effort strategy without specifically addressing glenohumeral stability may underestimate co-activation of the stabilizing rotator cuff muscles, and inaccurately predict that the contact force between the humerus and the glenoid is directed outside the articular surface of the joint. In this study, we compared existing stability models and proposed a new approach that penalized joint contact force whose direction deviates from the glenoid cavity center. We integrated these approaches into a muscle redundancy solver and estimated muscle and joint forces using the thoracoscapular shoulder musculoskeletal model. We compared model estimates to in vivo measurements of joint contact forces. We found that the penalty formulation reproduced the contact force direction most accurately, and promoted greater muscle co-contraction. These findings support the proposed penalty approach as a benchmark for more accurate analysis of shoulder biomechanics using musculoskeletal simulations.

Common optimization approaches for solving the muscle redundancy problem in musculoskeletal simulations can predict shoulder contact forces that either violate or barely satisfy joint stability requirements, with force directions falling outside or near the perimeter of the glenoid cavity. In this study, several glenohumeral stability formulations were tested against in vivo measurements of glenohumeral contact forces from the Orthoload dataset on one participant data in lateral, posterior, and anterior dumbbell raises. The investigated formulations either constrained the contact force direction to remain within different shapes of a stability perimeter, or added a penalty term that discouraged contact force directions from deviating from the glenoid cavity center. All stability formulations predicted contact force magnitudes that agreed relatively well to the in vivo measured forces except for the strictest formulation that constrained the joint contact force directly to the glenoid cavity center. Constraint and conditional penalty models estimated force vectors that largely lay along the perimeters. Continuous penalty models estimated relatively more accurate contact force directions within the glenoid cavity than constraint models. Our findings support the proposed penalty formulations as more reasonable and accurate than other investigated existing glenohumeral stability formulations.