Tunçel, OrkunAltun, KeremBarshan, Billur2016-02-082016-02-082009http://hdl.handle.net/11693/28726Date of Conference: 9-11 April 2009Conference Name: IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009In this study, eight different leg motions are classified using two single-axis gyroscopes mounted on the right leg of a subject with the help of several pattern recognition techniques. The methods of least squares, Bayesian decision, k-nearest neighbor, dynamic time warping, artificial neural networks and support vector machines are used for classification and their performances are compared. This study comprises the preliminary work for our future studies on motion recognition with a much wider scope.TurkishArtificial neural networkBayesian decisionDynamic time warpingK-nearest neighborsLeast squareMotion recognitionSingle-axisBayesian networksGyroscopesNeural networksPattern recognitionConference Paper10.1109/SIU.2009.5136404