Title :
Classification of leg motions by processing gyroscope signals
Author :
Tunçel, Orkun ; Altun, Kerem ; Barshan, Billur
Author_Institution :
Elektrik ve Elektron. Muhendisligi Bolumu, Bilkent Univ., Ankara
Abstract :
In 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.
Keywords :
Bayes methods; artificial intelligence; gyroscopes; least squares approximations; neural nets; pattern classification; pattern clustering; pattern recognition; support vector machines; Bayesian decision; artificial neural networks; dynamic time warping; gyroscope signal processing; k-nearest neighbor; least square methods; leg motion classification; motion recognition; pattern recognition techniques; support vector machines; Artificial neural networks; Bayesian methods; Gyroscopes; Least squares methods; Leg; Micromechanical devices; Pattern recognition; Signal processing; Support vector machine classification; Support vector machines;
Conference_Titel :
Signal Processing and Communications Applications Conference, 2009. SIU 2009. IEEE 17th
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-4435-9
Electronic_ISBN :
978-1-4244-4436-6
DOI :
10.1109/SIU.2009.5136404
