An examination of procedures for determining body segment attitude and position from noisy biomechanical data.

For the kinematic analysis of movement it is necessary to determine the position and attitude of rigid bodies in some specified reference frame. In biomechanics, these rigid bodies are usually segments of the human body, and the position of a distal segment is normally defined relative to a proximal segment. It was the purpose of this study to compare the accuracy of three approaches for the determination of the position and attitude of rigid bodies under four different noise conditions which were designed to model the conditions found in biomechanics studies. One technique investigated assumes the data are error free; another uses matrix algebra and employs matrix perturbation theory; and the third is a least-squares procedure. The evaluation was performed using a computer simulation which attempted to model 'typical' experimental conditions found in biomechanical studies. The attitude of the distal rigid body was defined using helical angles, with these angles being generated using a random number generator. All three techniques were assessed by their ability to predict a set of known helical angles and position vectors under different noise conditions. The study demonstrated that the least-squares technique was the most accurate for determining the attitude matrix and position vector for the cases investigated. None of the techniques investigated could allow for anisotropic noise conditions, yet anisotropic noise conditions are often obtained when using measurement procedures common in biomechanics. The study also highlighted the need to low-pass filter data prior to the computation of the position and attitude of rigid bodies.