Drift-Free Position Estimation for Periodic Movements Using Inertial Units

Latest advances in microelectromechanical systems have made inertial units (IUs) a powerful tool for human motion analysis. However, difficulties in handling their output signals must be overcome. The purpose of this study was to develop the novel "PB-algorithm" based on polynomial data fitting, splines interpolation, and the wavelet transform, one after the other, to cancel drift disturbances in position estimation for periodic movements. High-accuracy position measurements from an optical system (Vicon Nexus 1.0) were used to validate the proposed method and comparison with another drift-correction algorithm was provided. Results indicate the accuracy with respect to the Vicon's reference signal (euclidean error lower than 54.62 × 10(-3) m and correlation coefficient higher than 0.968). A reduction of the root-mean-square error of 68.74% was obtained when the proposed two-step method was compared with a modified-band limited Fourier linear combiner. All methods were applied to data from the 30-s chair stand test, which is one of the most used clinical tests dealing with lower body strength assessment, falls prediction, and gait disorders in older adults. The relevance of this study is that after cancelling drift disturbances, and obtaining an accurate Z-position estimation, it is possible to evaluate the sit-to-stand and stand-to-sit transitions from the whole test.