I used to do a bunch of this stuff in engineering school, and later with stress and vibration test results.

Spurious data points are usually removed using statistical methods, most commonly with the Student T distribution, particularly if the order of the system is known.

Rather than keeping track of a range, you want to use the data stream to keep track of the standard deviation of the samples. Using your estimated standard deviation, and a choice of how "sure" you want to be that a given point is an outlier, you can use a simple formula to detect them.

This might get you down the right track:

Studentized Residuals

On the other hand, if you don't have a statistics background, maybe not.

Here is a more friendly intro, with a link to a paper on the subject: Outliers

Best,

Jim