A calibrated EMG-informed neuromusculoskeletal model can estimate hip and knee joint contact forces in cycling better than static optimisation.

Abstract

Cycling is a popular competitive and recreational exercise and is recommended as safe to perform following hip or knee surgery. During cycling, joint contact forces (JCF) have been recorded in-vivo and estimated via neuromusculoskeletal models, but model estimates are yet to be validated. In this study, motion data, crank force, and electromyograms for a range of cadences (40 and 60 revolutions per minute (rpm)) and power outputs (25, 35, 50, 60, 79, 75, 85, 95, 120 W) were collected from 7 healthy people cycling on a powered stationary ergometer. A (1) calibrated electromyogram-informed neuromusculoskeletal model and an (2) uncalibrated model that utilised static optimisation were used to estimate hip and knee JCF. Hip and knee JCF estimates were compared against in-vivo measurements of hip and knee JCF from literature. Peak hip and knee JCF were overestimated by both electromyogram-informed and static optimisation solutions, however, the magnitude and gradients of JCF as a function of cadence and power estimated by the electromyogram-informed solution more closely matched in-vivo measurement than those computed by static optimisation. Similarly, the profile of knee JCF as a function of crank angle estimated by the electromyogram-informed solution more closely matched in-vivo knee JCF than the static optimisation solution. Results indicate electromyogram-informed modelling is a valid computational approach to estimate knee and hip biomechanics during standard seated ergometer cycling.