This prototype follows the idea of  where Harrison uses a microphone to record and recognize a set of defined gestures. In this implementation we follow the same approach by using the Dynamic Time Warp algorithm[2,3] but propose it under a different setting: the PureData programming environment.
This research for IMMI course at IST will result in a small decoupled system that is able to recognize a set of gestures and send the resulting gesture in a OSC formatted message, to be received in any connected system via network (either locally of remotely) – thus achieving modularity. For our experiments will be using it to recognized gestures performed by a DJ with his foot to control a DJ setup, can be used for many more applications (such as proposed by Harrison in).
Currently there is no implementation of the DTW algorithm for usage in PureData environment, although it has been proposed by Todoroff and Bettens  but still not ported to PureData, our implementation is based on on Andrew Slater and John Coleman’s DTW but ported to PureData with several needed modifications. The DTW object is still in alpha phase but it is already working and available for public usage here, the official release will be published later once the API is fully defined.
This shows a possible implementation of a DTW as a pd external – written in ANSI C. For this demo there are 8 samples that are used as gesture patterns, the algorithm tries to find the best gesture for the sampled input.
Hardware: lo-fi built-in microphone (very bad!)
Software: Puredata 0.41 (works with extended too.); Ubuntu 9.10; Jack Audio Server
Work by: Pedro Lopes and Guilherme Fernandes
 Harrison, Chris and Hudson, Scott E. Scratch Input: Creating Large, Inexpensive, Unpowered and Mobile finger Input Surfaces. In Proceedings of the 21st Annual ACM Symposium on User interface Software and Technology. UIST ’08. ACM, New York, NY, 205-208.
 Toward accurate dynamic time wrapping in linear time and space.. S. Salvador and P. Chan. Intelligent Data Analysis, 11(5):561-580, 2007.
 FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space. S. Salvador & P. Chan. KDD Workshop on Mining Temporal and Sequential Data, pp. 70-80, 2004
 Puckette, Miller Smith (2007). The Theory and Technique of Electronic Music. World Scientific Press, Singapore. ISBN 978-9812705419.
 Todor Todoroff , Fré́déric Bettens, REAL-TIME DTW-BASED GESTURE RECOGNITION EXTERNAL OBJECT FOR MAX/MSP AND PUREDATA , Sound Music Computing 2009, Oporto. Faculty of Engineering (FPMs) – TCTS Lab
 Andrew Slater and John Coleman’s DTW: –http://www.phon.ox.ac.uk/files/slp/Extras/dtw.html
 Github Repository for Pedro Lopes http://github.com/PedroLopes/PD-externals