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Thanks again to everyone that responded. My technical reference library
definitly needs some additions!
>From the replies I received, no one could tell me exactly what the effect
of a rolling average would be, except that it is a low-pass filter, and the
mathematical formula that describes it is called an FIR (Finite Impulse
Response) filter. An FIR filter is a polynomial that uses preceeding data
values to calculate the value of the current datum. A rolling average is a
special case of the FIR called a rectangular filter. By adjusting the
coeffecients of the polynomial, as well as the number of terms (order), a
low pass, band pass, or high pass filter may be created.
The math that goes into calculating the values of the coeffecents is well
beyond the scope of a single maillist posting, however I am told that
Matlab has features that make these calculations very easy.
In my specific case, I am sampling at 100Hz, and need a low pass filter to
eliminate everything above 10Hz. I used a 10 point (or 10 "tap") FIR
rectangular filter, each coeffecient having the value of 0.1 . Since I am
looking at postural sway, I think the filtering of data higher in frequency
that 10Hz will not introduce any errors.
Dan Major
Univ. of Okla. School of Industrial Engineering
major@ou.edu htp://www.ecn.ou.edu/~major
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definitly needs some additions!
>From the replies I received, no one could tell me exactly what the effect
of a rolling average would be, except that it is a low-pass filter, and the
mathematical formula that describes it is called an FIR (Finite Impulse
Response) filter. An FIR filter is a polynomial that uses preceeding data
values to calculate the value of the current datum. A rolling average is a
special case of the FIR called a rectangular filter. By adjusting the
coeffecients of the polynomial, as well as the number of terms (order), a
low pass, band pass, or high pass filter may be created.
The math that goes into calculating the values of the coeffecents is well
beyond the scope of a single maillist posting, however I am told that
Matlab has features that make these calculations very easy.
In my specific case, I am sampling at 100Hz, and need a low pass filter to
eliminate everything above 10Hz. I used a 10 point (or 10 "tap") FIR
rectangular filter, each coeffecient having the value of 0.1 . Since I am
looking at postural sway, I think the filtering of data higher in frequency
that 10Hz will not introduce any errors.
Dan Major
Univ. of Okla. School of Industrial Engineering
major@ou.edu htp://www.ecn.ou.edu/~major
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To unsubscribe send SIGNOFF BIOMCH-L to LISTSERV@nic.surfnet.nl
For information and archives: http://isb.ri.ccf.org/biomch-l
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