Classification of leg motions by processing gyroscope signals
| Autor: | Billur Barshan, Kerem Altun, Orkun Tuncel |
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| Rok vydání: | 2009 |
| Předmět: |
Artificial neural network
Dynamic time warping Computer science Gyroscopes Least square Least squares Bayesian decision law.invention k-nearest neighbors algorithm K-nearest neighbors law Pattern recognition Signal processing Single-axis business.industry Gyroscope Support vector machine Bayesian networks Motion recognition Pattern recognition (psychology) Artificial intelligence business Neural networks |
| Zdroj: | Proceedings of the IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 |
| Popis: | Date of Conference: 9-11 April 2009 Conference Name: IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 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. |
| Databáze: | OpenAIRE |
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