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QuickSAND update (was Re: Extrapolation techniques to fill gapsin movement data)

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  • QuickSAND update (was Re: Extrapolation techniques to fill gapsin movement data)

    1. I had added an interpolation routine to my QuickSAND program for
    myself but had not put
    the new version on the web. This is now done. The interpolation is
    based on the parameters
    set for the spline routine and will interpolate to either a new
    number of points or to a new
    sampling frequency.

    QuickSAND (Quick Smoothing and Numerical Differentiation) is a quick and
    friendly freeware program for the Power Macintosh. Available at

    http://jaw.fmnh.org/Software/programs.html

    2. Based on how I understand your question, It seems you want to
    interpolate missing values
    located between known values but are doing this by extrapolation from
    the previous values.
    The spline routine avoids this by interpolating based on values before
    and after the missing
    value. The spline routine can have unequally space points (hence
    missing values) and the GCV
    criterion to find the smoothing parameter should be good for
    interpolating missing values
    since this is essentially what cross-validation is doing. If you truly
    want to extrapolate you
    might want to try linear prediction, which is described, among other
    places, in the Numerical
    Recipes books.

    Hope this helps

    Jeff

    >Hello BIOMCH-L readers,
    >
    >I am working in gait biomechanics and am writing code to fill in missing
    >data from streams of 3-dimensional co-ordinate data. Our system generates
    >0 values in the co-ordinate file when a marker is out of camera-system
    >view. Thus far I have tried polynomial curve fitting of varying orders
    >based on datapoints prior to the missing value, and extrapolating the
    >value. This method only met with limited success as the movement in
    >different axes has behaviour of different (polynomial curve) orders. If
    >the gap of missing markers is too large, the extrapolated point estimation
    >diverges greatly, depending on the order of the polynomial fit.
    >
    >The second method I have tried is to fit a cubic spline to datapoints
    >prior to the missing point in question. This is met with limited success.
    >
    >Questions:
    >
    >1. Most, if not all interpolation procedures that I know of require
    >equally spaced data; thus if there is a gap in ones dataset, a polynomial
    >curve or spline cannot be fit to the dataset! Could anyone confirm this
    >statement?
    >
    >2. I would like to know from individuals that use movement data (gait and
    >others), what types of extrapolation or curve-fitting procedures are
    >commonly being used.
    >
    >3. Does anyone know of a 3-dimensional spline technique whereby one can
    >utilize all x,y,z co-ordinate data to extrapolate the next point(s)!
    >
    >I will post a follow-up with replies.
    >
    >Thanks
    >
    >Alan Morris
    >Research Engineer - Gait Laboratory
    >Bloorview MacMillan Centre
    >350 Rumsey Road
    >Toronto, Ontario
    >CANADA
    >M4G-1R8
    >Tel (416) 425-6220 x3508
    >Fax (416) 425-1634
    >email morrisa@ecf.utoronto.ca
    >
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    -------------
    Jeff Walker
    Dept. of Zoology
    Field Museum of Natural History
    Roosevelt Rd. at Lake Shore Dr.
    Chicago, IL 60605, USA
    phone: 312-922-9410 x537 fax: 312-427-7269
    e-mail: walker@fmppr.fmnh.org
    URL: http://jaw.fmnh.org/Home.html

    "This could be a fundamental advantage of jet propulsion,
    at least for a scallop."

    - From the abstract of Cheng, J-Y., I.G. Davison and M.E. DeMont (1996) J.
    Exp. Biol. 199:1931-1946.
    ---------------------------------------------------------------

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