Differentiation of human motion data using combined spline and least squares concepts.
A differentiation method, which combines the concepts of least squares and splines, has been developed to analyze human motion data. This data smoothing technique is not dependent on a choice of a cut-off frequency and yet it closely reflects the nature of the phenomenon. Two sets of published benchmark data were used to evaluate the new algorithm.
Department of Mathematics, West Virginia University, Morgantown 26506.
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W
Simons
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Yang
D000465:Algorithms; D003627:Data Interpretation, Statistical; D006801:Humans; D016018:Least-Squares Analysis; D009068:Movement / Q000502:physiology*