What you're describing may be related to gesture recognition techniques, so you could search on them for ideas.
The obvious approach is to apply a curve fit, but that will have the effect of smoothing away all the interesting details and kinks. Another approach suggested is to look at speeds and accelerations, but that can get hairy (direction changes can be very fast or very slow and deliberate)
A fairly basic but effective approach is to simplify the samples directly into a polyline.
For example, work your way through the samples (e.g.) from sample 1 to sample 4, and check if all 4 samples lie within a reasonable error of the straight line between 1 & 4. If they do, then extend this to points 1..5 and repeat until such a time as the straight line from the start point to the end point no longer provides a resonable approximation to the curve defined by those samples. Create a line segment up to the previous sample point and start accumulating a new line segment.
You have to be careful about your thresholds when the samples are too close to each other, so you might want to adjust the sensitivity when regarding samples fewer than 4-5 pixels away from each other.
This will give you a set of straight lines that will follow the original path fairly accurately.
If you require additional smoothing, or want to create a scalable vector graphic, then you can then curve-fit from the polyline. First, identify the kinks (the places in your polyline where the angle between one line and the next is sharp - e.g. anything over 140 degrees is considered a smooth curve, anything less than that is considered a kink) and break the polyline at those discontinuities. Then curve-fit each of these sub-sections of the original gesture to smooth them. This will have the effect of smoothing the smooth stuff and sharpening the kinks. (You could go further and insert small smooth corner fillets instead of these sharp joints to reduce the sharpness of the joins)
Brute force, but it may just achieve what you want.