This paper provides an overview of forward dynamic neuromusculoskeletal modeling. The aim of such models is to estimate or predict muscle forces, joint moments, and/or joint kinematics from neural signals. This is a four-step process. In the first step, muscle activation dynamics govern the transformation from the neural signal to a measure of muscle activation-a time varying parameter between 0 and 1. In the second step, muscle contraction dynamics characterize how muscle activations are transformed into muscle forces. The third step requires a model of the musculoskeletal geometry to transform muscle forces to joint moments. Finally, the equations of motion allow joint moments to be transformed into joint movements. Each step involves complex nonlinear relationships. The focus of this paper is on the details involved in the first two steps, since these are the most challenging to the biomechanician. The global process is then explained through applications to the study of predicting isometric elbow moments and dynamic knee kinetics. Keywords Hill model; EMG; tendon; musculotendon complex; pennation angleThe eight-syllable term neuromusculoskeletal in the title of this article simply means that we will be modeling the movements produced by the muscular and skeletal systems as controlled by the nervous system. Neuromusculoskeletal modeling is important for studying functional electrical stimulation of paralyzed muscles, for designing prototypes of myoelectrically controlled limbs, and for general study of how the nervous system controls limb movements in both unimpaired people and those with pathologies such as spasticity induced by stroke or cerebral palsy.There are two fundamentally different approaches to studying the biomechanics of human movement: forward dynamics and inverse dynamics. Either approach can be used to determine joint kinetics (e.g., estimate joint moments during movements) and it is important that the differences between them are understood.NIH Public Access

To study abnormal spatial patterns of muscle activation in hemiparetic stroke, we compared EMG activity in paretic and contralateral elbow and shoulder muscles of 10 hemiparetic subjects during 1.5-s voluntary isometric contractions, against five to eight different loads. Isometric forces were generated in eight directions, referenced to a plane orthogonal to the long axis of the forearm, and were recorded by a three degrees of freedom load cell, mounted at the wrist. Surface and intramuscular EMGs of six elbow and six shoulder muscles were recorded from both impaired and contralateral upper extremities of each subject. The spatial characteristics of EMG activation of individual muscles were summarized using two measures. The first, called the 'net resultant EMG vector' is a new measure which calculated the vector sum of EMG magnitudes for each of the eight directions, and the second, index of EMG focus, is a measure of the range of EMG activation recorded for each load level. Use of these measures permitted us to describe spatial EMG characteristics quantitatively, which has not been done previously. We observed consistent and statistically significant shifts in the resultant EMG vector directions in the impaired limb, especially in shoulder and other proximal muscles. Significant increases in the angular range of EMG activity were also identified and were most evident at the elbow. Correlation analysis techniques were used to assess the degree of coactivation of different muscle pairs. There were consistent EMG coactivation patterns observed across all subjects (both normal and hemiparetic). However, in spasticparetic limbs, additional novel coactivational relationships were also recorded, especially between elbow flexors/shoulder abductors and elbow extensors/shoulder adductors. These novel coactivation patterns represent a reduction in the number of possible muscle combinations, or in the number of possible 'synergies' in the paretic limb of the stroke subject. This reduction in number of 'synergies' could result from a loss of descending command options; from an increased reliance on residual, descending brainstem pathways (such as the reticulospinal and vestibulospinal projections); from changes in spinal interneuronal excitability; or from a combination of several of these factors. The relative merits of these hypotheses are addressed.

Some individuals can stabilize their knees following anterior cruciate ligament rupture even during activities involving cutting and pivoting (copers), others have instability with daily activities (non-copers). Movement and muscle activation patterns of 11 copers, ten non-copers and ten uninjured subjects were studied during walking and jogging. Results indicate that distinct gait adaptations appeared primarily in the non-copers. Copers used joint ranges of motion, moments and muscle activation patterns similar to uninjured subjects. Non-copers reduced their knee motion, and external knee flexion moments that correlated well with quadriceps strength. Non-copers also achieved peak hamstring activity later in the weight acceptance phase and used a strategy involving more generalized co-contraction. Both copers and non-copers had high levels of quadriceps femoris muscle activity. The reduced knee moment in the involved limbs of the non-copers did not represent "quadriceps avoidance" but rather represented a strategy of general co-contraction with a greater relative contribution from the hamstring muscles.

No abstract

Background Anterior cruciate ligament (ACL) injury predisposes individuals to early-onset knee joint osteoarthritis (OA). Abnormal joint loading is apparent after ACL injury and reconstruction. The relationship between altered joint biomechanics and the development of knee OA is unknown. Hypothesis Altered knee joint kinetics and medial compartment contact forces initially after injury and reconstruction are associated with radiographic knee OA 5 years after reconstruction. Study Design Case-control study; Level of evidence, 3. Methods Individuals with acute, unilateral ACL injury completed gait analysis before (baseline) and after (posttraining) preoperative rehabilitation and at 6 months, 1 year, and 2 years after reconstruction. Surface electromyographic and knee biomechanical data served as inputs to an electromyographically driven musculoskeletal model to estimate knee joint contact forces. Patients completed radiographic testing 5 years after reconstruction. Differences in knee joint kinetics and contact forces were compared between patients with and those without radiographic knee OA. Results Patients with OA walked with greater frontal plane interlimb differences than those without OA (nonOA) at baseline (peak knee adduction moment difference: 0.00 ± 0.08 N·m/kg·m [nonOA] vs −0.15 ± 0.09 N·m/kg·m [OA], P = .014; peak knee adduction moment impulse difference: −0.001 ± 0.032 N·m·s/kg·m [nonOA] vs −0.048 ± 0.031 N·m·s/kg·m [OA], P = .042). The involved limb knee adduction moment impulse of the group with osteoarthritis was also lower than that of the group without osteoarthritis at baseline (0.087 ± 0.023 N·m·s/kg·m [nonOA] vs 0.049 ± 0.018 N·m·s/kg·m [OA], P = .023). Significant group differences were absent at posttraining but reemerged 6 months after reconstruction (peak knee adduction moment difference: 0.02 ± 0.04 N·m/kg·m [nonOA] vs −0.06 ± 0.11 N·m/kg·m [OA], P = .043). In addition, the OA group walked with lower peak medial compartment contact forces of the involved limb than did the group without OA at 6 months (2.89 ± 0.52 body weight [nonOA] vs 2.10 ± 0.69 body weight [OA], P = .036). Conclusion Patients who had radiographic knee OA 5 years after ACL reconstruction walked with lower knee adduction moments and medial compartment joint contact forces than did those patients without OA early after injury and reconstruction.

No abstract

No abstract

Greater varus-valgus laxity in the uninvolved knees of OA patients versus older control knees and an age-related increase in varus-valgus laxity support the concept that some portion of the increased laxity of OA may predate disease. Loss of cartilage/bone height is associated with greater varus-valgus laxity. These results raise the possibility that varus-valgus laxity may increase the risk of knee OA and cyclically contribute to progression.