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Correspondence

The selection of filtering and differentiating techniques for biomechanical data

Pages 175-177 | Accepted 15 Feb 1989, Published online: 14 Nov 2007

References

  • Challis , J.H. and Kerwin , D.G. 1988 . Optimal filtering and differentiation of biomechanical data using cross‐validated splines . Journal of Sport Sciences , 6 : 152
  • Dohrmann , C.R. , Busby , H.R. and Trujillo , D.M. 1988 . Smoothing noisy data using dynamic programming and generalized cross‐validation . Journal of Biomechanical Engineering , 110 : 37 – 41 .
  • Hatze , H. 1988 . The use of optimally regularized Fourier series for estimating higher order derivatives of noisy biomechanical data . Journal of Biomechanics , 14 : 13 – 18 .
  • Lanshammar , H. 1982 . On practical evaluation of differentiation techniques for human gait analysis . Journal of Biomechanics , 15 : 99 – 105 .
  • Pezzack , J.C. , Norman , R.W. and Winter , D.A. 1977 . An assessment of derivative determining techniques used for motion analysis . Journal of Biomechanics , 10 : 377 – 82 .
  • Utreras , F. 1980 . Sur le choix de parametre d'adjustement dans le lissage par fonctions spline . Numerischen Mathematik , 34 : 15 – 28 .
  • Woltring , H.J. 1986 . A Fortran package for generalized, cross‐validatory spline smoothing and differentiation . Advances in Engineering Software , 8 : 104 – 13 .

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