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 dynamicsgovern 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 dynamicscharacterize how muscle activations are transformed into muscle forces. The third step requires a model of themusculoskeletal geometryto transform muscle forces to joint moments. Finally, theequations of motionallow 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.

Impairment of the human neuromusculoskeletal system can lead to significant mobility limitations and decreased quality of life. Computational models that accurately represent the musculoskeletal systems of individual patients could be used to explore different treatment options and optimize clinical outcome. The most significant barrier to model‐based treatment design is validation of model‐based estimates of in vivo contact and muscle forces. This paper introduces an annual “Grand Challenge Competition to Predict In Vivo Knee Loads” based on a series of comprehensive publicly available in vivo data sets for evaluating musculoskeletal model predictions of contact and muscle forces in the knee. The data sets come from patients implanted with force‐measuring tibial prostheses. Following a historical review of musculoskeletal modeling methods used for estimating knee muscle and contact forces, we describe the first two data sets used for the first two competitions and summarize four subsequent data sets to be used for future competitions. These data sets include tibial contact force, video motion, ground reaction, muscle EMG, muscle strength, static and dynamic imaging, and implant geometry data. Competition participants create musculoskeletal models to predict tibial contact forces without having access to the corresponding in vivo measurements. These blinded predictions provide an unbiased evaluation of the capabilities and limitations of musculoskeletal modeling methods. The paper concludes with a discussion of how these unique data sets can be used by the musculoskeletal modeling research community to improve the estimation of in vivo muscle and contact forces and ultimately to help make musculoskeletal models clinically useful. © 2011 Orthopaedic Research Society. © 2011 Orthopaedic Research Society Published by Wiley Periodicals, Inc. J Orthop Res 30:503–513, 2012

BESIER, T. F., D. G. LLOYD, J. L. COCHRANE, and T. R. ACKLAND. External loading of the knee joint during running and cutting maneuvers. Med. Sci. Sports Exerc., Vol. 33, No. 7, 2001, pp. 1168–1175. To investigate the external loads applied to the knee joint during dynamic cutting tasks and assess the potential for ligament loading. A 50-Hz VICON motion analysis system was used to determine the lower limb kinematics of 11 healthy male subjects during running, sidestepping, and crossover cut. A kinematic model was used in conjunction with force place data to calculate the three-dimensional loads at the knee joint during stance phase. External flexion/extension loads at the knee joint were similar across tasks; however, the varus/valgus and internal/external rotation moments applied to the knee during sidestepping and crossover cutting were considerably larger than those measured during normal running (P < 0.05). Sidestepping tasks elicited combined loads of flexion, valgus, and internal rotation, whereas crossover cutting tasks elicited combined loads of flexion, varus, and external rotation. Compared with running, the potential for increased ligament loading during sidestepping and crossover cutting maneuvers is a result of the large increase in varus/valgus and internal/external rotation moments rather than any change in the external flexion moment. The combined external moments applied to the knee joint during stance phase of the cutting tasks are believed to place the ACL and collateral ligaments at risk of injury, particularly at knee flexion angles between 0° and 40°, if appropriate muscle activation strategies are not used to counter these moments.

BESIER, T. F., D. G. LLOYD, T. R. ACKLAND, and J. L. COCHRANE. Anticipatory effects on knee joint loading during running and cutting maneuvers. Med. Sci. Sports Exerc., Vol. 33, No. 7, 2001, pp. 1176–1181. To determine how unanticipated performance of cutting maneuvers in sport affects the external loads applied to the knee joint and the potential risk for ligament injury. A 50-Hz VICON motion analysis system was used to determine the lower limb kinematics of 11 healthy male subjects during running and cutting tasks performed under preplanned (PP) and unanticipated (UN) conditions. Subjects performed the UN tasks in response to a light stimulus on a target board. A kinematic model was then used in conjunction with force place data to calculate the three-dimensional loads at the knee joint. External flexion/extension moments at the knee joint were similar between PP and UN conditions; however, the varus/valgus and internal/external rotation moments during the UN cutting tasks were up to twice the magnitude of the moments measured during the PP condition. Cutting maneuvers performed without adequate planning may increase the risk of noncontact knee ligament injury due to the increased external varus/valgus and internal/external rotation moments applied to the knee. These results are probably due to the small amount of time to make appropriate postural adjustments before performance of the task, such as the position of the foot on the ground relative to the body center of mass. Subsequently, training for the game situation should involve drills that familiarize players with making unanticipated changes of direction. Practice sessions should also incorporate plyometrics and should focus on better interpretation of visual cues to increase the time available to preplan a movement.