My goal is to recognize simple gestures from accelerometers mounted on a sun spot. A gesture could be as simple as rotating the device or moving the device in several differ
What hasn't been mentioned yet is the actual gesture recognition. This is the hard part. After you have cleaned up your data (low pass filtered, normalized, etc) you still have most of the work to do.
Have a look at Hidden Markov Models. This seems to be the most popular approach, but using them isn't trivial. There is usually a preprocessing step. First doing STFT and clustering the resultant vector into a dictionary, then feeding that into a HMM. Have a look at jahmm in google code for a java lib.