@conference { aws-svm-prtouch,
	title = {Support Vector Machine Learning for Gesture Signal Estimation with a Piezo Resistive Fabric Touch Surface},
	booktitle = {NIME},
	year = {2010},
	note = {Draft paper in submission. Do not redistribute without permission.},
	address = {Sydney, Australia},
	abstract = {The design of an unusually simple fabric-based touch and pressure sensor is introduced. An analysis of the raw sensor data is shown to have significant non-linearities and non-uniform noise. Using support vector machine learning and a state-dependent adaptive filter it is demonstrated that these problems can be overcome. The method is evaluated quantitatively using a statistical estimate of the instantaneous rate of information transfer. The SVM regression alone is shown to improve the gesture signal information rate by up to 20\% with zero added latency, and in combination with filtering by 40\% subject to a constant latency bound of 10 milliseconds.},
	author = {Schmeder, Andrew and Freed, Adrian}
}
