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Overuse knee injuries are common in bicycling and are often attributed to poor bicycle-fit. Bicycle-fit for knee health focuses on setting saddle height to elicit a minimum knee flexion angle of 25-40°. Equations to predict saddle height include a single input, resulting in a likely suboptimal bicycle-fit. The purpose of this work was to develop an equation to predict saddle height from anthropometrics, bicycle geometry, and user-defined joint kinematics. Methods: Forty healthy adults (17 women, 23 men; mean (SD): 28.6 (7.2) years; 24.2 (2.6) kg/m2) participated. Kinematic analyses were conducted for 18 three-minute bicycling bouts including all combinations of 3 horizontal and 3 vertical saddle positions, and 2 crank arm lengths. For both minimum and maximum knee flexion, predictors were identified using Least Absolute Shrinkage and Selection Operator (LASSO) regression, and final models were fit using linear regression. Secondary analyses determined if saddle height equations were sex dependent. Results: The equation to predict saddle position from minimum knee flexion angle (R2=0.97; root mean squared error (RMSE) = 1.15 cm) was: Saddle height (cm) = 7.41 + 0.82(inseam cm) – 0.1(minimum knee flexion °) + 0.003(inseam cm)(seat tube angle °). The maximum knee flexion equation (R2=0.97; RMSE=1.15 cm) was: Saddle height (cm) = 41.63 + 0.78(inseam cm) – 0.25(maximum knee flexion °) + 0.002(inseam cm)(seat tube angle °). The saddle height equations were not dependent on sex. Conclusions: These equations provide a novel, practical strategy for bicycle-fit that accounts for rider anthropometrics, bicycle geometry and user-defined kinematics. Highlights This work developed simple equations to prescribed bicycle saddle height that elicits desired knee kinematics. Separate equations are presented for prescribing minimum or maximum knee flexion angle. Equations can be generalized to riders of both sexes, and a breadth of anthropometrics and ages. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to establish normative diffusion tensor imaging (DTI) eigenvalues (λ1,λ2,λ3), apparent diffusion coefficient, and fractional anisotropy in asymptomatic foot muscles., Methods: Ten healthy adults (mean [SD], 25.9 [4.3] years) were examined using a 3-T magnetic resonance imaging scanner. Diffusion tensor imaging indices were evaluated in 5 muscles in the foot: quadratus plantae, abductor hallucis, flexor hallucis brevis, flexor digitorum brevis, and abductor digiti minimi. Signal-to-noise ratio was also measured for each muscle., Results: In the various foot muscles, λ1 ranged from 1.88 × 10 to 2.14 × 10 mm/s, λ2 ranged from 1.39 × 10 to 1.48 × 10 mm/s, and λ3 ranged from 0.91 × 10 to 1.27 × 10 mm/s; apparent diffusion coefficient ranged from 1.48 × 10 to 1.55 × 10 mm/s; and fractional anisotropy ranged from 0.21 to 0.40. Statistical differences were seen in some eigenvalues between muscle pairs. Mean signal-to-noise ranged from 47.5 to 69.1 in the various muscles examined., Conclusions: Assessment of anisotropy of water diffusion in foot muscles was feasible using DTI. The measured DTI metrics in the foot were similar to those in calf and thigh skeletal muscles.