Side-to-side asymmetry in lower limb strength and hamstring-quadriceps strength ratio among collegiate American football players.

[Purpose] The present study aimed to investigate the lower limbs injury risk factors that are based on conventional Hamstring to Quadriceps ratio and limb asymmetry index in varsity American football players. [Participants and Methods] Twenty-six varsity American football players aged 19-27 years and with 2.31 ± 1.29 years of American football experience from Dogu Akdeniz University volunteered to undergo measurements of average peak torque for isokinetic flexion and extension of dominant limb and non-dominant limb at 60°·s-1 and 300°·s-1. Hamstring to Quadriceps ratio and limb asymmetry index were also calculated for Hamstring and Quadriceps muscles. [Results] Statistical analysis revealed that dominant Quadriceps is stronger than non-dominant Quadriceps at 60°·s-1 speed. No statistical difference was found between dominant and non-dominant Hamstring peak torque at 60°·s-1 . Hamstring to Quadriceps ratio determined as normal both for 60°·s-1 and 300°·s-1according to the currently reported cut off value (H:Q ratio >60). Hamstring and Quadriceps limb asymmetry index also determined as normal (cut off value for LSI 10%) at 60°·s-1. However, for both Hamstring and Quadriceps, side- to- side strength asymmetry at 300°·s-1 was observed. [Conclusion] To prevent possible lower limb injury and to increase performance, varsity American football players who are actively training and competing might consider taking strength asymmetry into account to tailor their strength training program accordingly.

A novel adaptive time delay identification technique.

In this work, a novel online adaptive time delay identification method is proposed for a class of signal processing and communication applications, where the received signal is a combination of the transmitted signal and its delayed forms with the delay values being uncertain and required to be estimated. The design relies on a filtered form of a prediction error-like term which is then used in the design of the novel nonlinear adaptive update law. The stability of the identification algorithm is then investigated via novel Lyapunov based tools and the time delay identification is proven to be globally uniformly ultimately bounded. Several numerical simulations are conducted to evaluate the performance of the proposed identifier where constant, slowly varying and suddenly changing delays are successfully identified even in the presence of additive noise.