Design of an adaptive accelerometer-based handwriting recognition system based on metacognitive framework

We present in this paper a software system that can provide highly adaptive accelerometer-based gesture recognition on commercial products. The algorithm features efficient motion detection, template matching-based motion pattern recognition, and template set optimization techniques. We apply our algorithm for recognizing 26 uppercase English alphabets with promising results.