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Summary optotrak differentiating method

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  • Summary optotrak differentiating method


    Some time ago we contacted the biomch-l
    network to find poeple that are familiar with the optotrak-
    system. We were having trouble with differentiating twice
    using the DAP.
    It turned out that the noise generated by the optotrak was
    causing the problem.
    Because debating the problem on the network sending the
    discussions to everyone attached seemed a bit unfriendly as
    not everyone migth be interested. So we now present you the
    results of our research in improving the software
    possibilities. We want to thank everyone who spend the time in
    helping us and discussing with us.
    The DAP (Data Analysis Package) is limited in its
    possibilities to differentiate as it has only acces to a few
    filters. With exception of the 3-point central method these
    all amplified the noise; worsening the problem. Although this
    method reduced the noise, it also reduced the signal amplitude
    by demping it. As the signal frequency enlarges this problem
    becomes bigger.
    Thus the DAP is virtually useless if you want to determine the
    highest acceleration acchieved by a subject who is bending its
    elbow. The noise of the signal is getting the overhand and the
    data you want to know disappears.
    We were adviced to switch over to Matlab and use this instead
    of DAP. This good advice spared us a lot of annoyance.
    Before the raw data can be read in Matlab we had to convert it
    into 3D-data and then into an Matlab.m-file.
    Whit the knowledge that the differentiating methods provided
    in DAP were not ideal we developped a method that is based on
    3 steps:
    First we filter out all frequencies above 50 Hz
    Secondly we differentiate the remaining signal by using the
    mathematical differentiating definition
    Thirdly we correct for the demping of the signal caused by
    this differentiating technique.
    The result of this approach is that with a perfect noiseless
    signal the accuracy in the range 0-50 Hz is better than
    99.99%. The noise was reduced to 20% of the original.

    We were very pleased with all the help we got and hope that
    anyone interested or copeing with the same problem can find
    anything usefull in this summary.

    greetings from
    Liek Voorbij and Jari Bonte
    Ir. A.I.M. Voorbij (MSc)
    Delft University of Technology
    Fac. of Industrial Design Engineering
    Dept. System and Product Ergonomics
    Jaffalaan 9
    2628 BX Delft
    The Netherlands
    Phone: +31 15 2785196
    Telefax: +31 15 2787179