Improvement of upper extremity kinematics estimation using a subject-specific forearm model implemented in a kinematic chain

Human movement reconstruction is still difficult due to noise generated by the use of skin markers. The a priori definition of a kinematic chain associated with a global optimisation method allows reducing these deleterious effects. When dealing with the forearm, this approach can be improved by personalising the two axes of rotation because their common modelling is not representative of joint geometry. The aim of the present study is to evaluate the kinematic effects of personalising these two axes of rotation, determined by a functional method and implemented in a kinematic chain (AXIS model).The AXIS model was compared with a reference model (ISB model), in which the forearm axes of rotation were defined according to the recommendations of the International Society of Biomechanics. The kinematic comparison (15 subjects and 3 tasks) was based on marker residuals (actual versus model-determined), joint kinematic root mean square differences (AXIS versus ISB) and joint amplitudes (AXIS versus ISB).The AXIS model improved the pose of the forearm and hand. The reduction in marker residuals for these segments ranged between 23% and 60%. The use of a functional method was also beneficial in personalising the flexion–extension and pronation–supination axes of the forearm. The contribution of pronation–supination, in terms of joint amplitudes, was increased by 15% during the specific task.The approach developed in this study is all the more interesting since this forearm model could be integrated into a kinematic chain to be used with a global approach becoming increasingly popular in biomechanics.