Equations to Prescribe Bicycle Saddle Height based on Desired Joint Kinematics and Bicycle Geometry

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 degrees. 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/m(2)) 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 (R-2=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 degrees) + 0.003(inseam cm)(seat tube angle degrees). The maximum knee flexion equation (R-2=0.97; RMSE=1.15 cm) was: Saddle height (cm) = 41.63 + 0.78(inseam cm) - 0.25(maximum knee flexion degrees) + 0.002(inseam cm)(seat tube angle degrees). 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.

Automated summary

This study developed equations to predict saddle height, taking into account rider anthropometrics, bicycle geometry, and user-defined joint kinematics.