TY - JOUR
T1 - Assessing manual lifting tasks based on segment angle interpolations
AU - Chang, C.C.
AU - Xu, X.
AU - Faber, G.S.
AU - Kingma, I.
AU - Dennerlein, J.T.
PY - 2012
Y1 - 2012
N2 - This study investigates the effects of the number of interpolation points on the prediction accuracy of segment angle trajectory during lifting. Ten participants performed various lifting tasks while a motion tracking system recorded their movements. Two-point through ten-point equal time-spaced segment angles extracted from major segment trajectory data captured by the motion tracking system were used to re-generate the whole body lifting motion by using polynomial and cubic spline interpolation methods. The root mean square error (RMSE) between the reference (motion tracking system) and the estimated (interpolation method) segment angle trajectories were calculated to quantify the prediction accuracy. The results showed that the cubic spline interpolation will yield a smaller RMSE value than one based on the polynomial interpolation. While increasing the number of interpolation points can reduce the RMSE of the estimated segment angle trajectories, there was a diminishing advantage in continuing to add interpolation points. A sensitivity analysis suggests that if the estimation of the segment angles at each interpolation point deviates considerably from the real value, and cannot be controlled at a low level (<10), the use of higher number of interpolation points will not improve the estimation accuracy. © 2012 - IOS Press and the authors. All rights reserved.
AB - This study investigates the effects of the number of interpolation points on the prediction accuracy of segment angle trajectory during lifting. Ten participants performed various lifting tasks while a motion tracking system recorded their movements. Two-point through ten-point equal time-spaced segment angles extracted from major segment trajectory data captured by the motion tracking system were used to re-generate the whole body lifting motion by using polynomial and cubic spline interpolation methods. The root mean square error (RMSE) between the reference (motion tracking system) and the estimated (interpolation method) segment angle trajectories were calculated to quantify the prediction accuracy. The results showed that the cubic spline interpolation will yield a smaller RMSE value than one based on the polynomial interpolation. While increasing the number of interpolation points can reduce the RMSE of the estimated segment angle trajectories, there was a diminishing advantage in continuing to add interpolation points. A sensitivity analysis suggests that if the estimation of the segment angles at each interpolation point deviates considerably from the real value, and cannot be controlled at a low level (<10), the use of higher number of interpolation points will not improve the estimation accuracy. © 2012 - IOS Press and the authors. All rights reserved.
U2 - 10.3233/WOR-2012-0465-2360
DO - 10.3233/WOR-2012-0465-2360
M3 - Article
VL - 41
SP - 2360
EP - 2363
JO - Work: A Journal of Prevention, Assessment and Rehabilitation
JF - Work: A Journal of Prevention, Assessment and Rehabilitation
SN - 1051-9815
IS - Suppl 1
ER -