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Kevin Deschamps, Giovanni Matricali, Maarten Eerdekens, Sander Wuite, Alberto Leardini and Filip Staes

Foot structure and kinematics have long been considered as risk factors for foot and lower-limb running injuries. The authors aimed at investigating foot joint kinetics to unravel their receptive and propulsive characteristics while running barefoot, both with rearfoot and with midfoot striking strategies. Power absorption and generation occurring at different joints of the foot in 6 asymptomatic adults were calculated using both a 3-segment and a 4-segment kinetic model. An inverse dynamic approach was used to quantify mechanical power. Major power absorption and generation characteristics were observed at the ankle joint complex as well as at the Chopart joint in both the rearfoot and the midfoot striking strategies. The power at the Lisfranc joint, quantified by the 4-segment kinetic model, was predominantly generated in both strategies, and at the toes, it was absorbed. The overall results show a large variability in the receptive and propulsive characteristics among the analyzed joints in both striking strategies. The present study may provide novel insight for clinical decision making to address foot and lower-limb injuries and to guide athletes in the adoption of different striking strategies during running.

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Rahman Davoodi and Gerald E. Loeb

Computer models of the neuromusculoskeletal systems can be used to study different aspects of movement and its control in humans and animals. SIMM with Dynamics Pipeline (Musculographics Inc., Chicago) and SD-Fast (Symbolic Dynamics Inc., Mountain View, CA) are software packages commonly used for graphic and dynamic simulation of movement in musculoskeletal systems. Building dynamic models with SIMM requires substantial C programming, however, which limits its use. We have developed Musculoskeletal Modeling in Simulink (MMS) software to convert the SIMM musculoskeletal and kinetics models to Simulink (Mathworks Inc., Natick, MA) blocks. In addition, MMS removes SIMM’s run-time constraints so that the resulting blocks can be used in simulations of closed-loop sensorimotor control systems.