Sensors | |
Classifying Human Leg Motions with Uniaxial Piezoelectric Gyroscopes | |
Orkun Tunl1  Kerem Altun1  | |
[1] Department of Electrical and Electronics Engineering, Bilkent University, Bilkent 06800 Ankara, Turkey; | |
关键词:
gyroscope;
inertial sensors;
motion classification;
Bayesian decision making;
rule-based algorithm;
least-squares method;
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DOI : 10.3390/s91108508 | |
来源: mdpi | |
【 摘 要 】
This paper provides a comparative study on the different techniques of classifying human leg motions that are performed using two low-cost uniaxial piezoelectric gyroscopes worn on the leg. A number of feature sets, extracted from the raw inertial sensor data in different ways, are used in the classification process. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), a rule-based algorithm (RBA) or decision tree, least-squares method (LSM),
【 授权许可】
CC BY
© 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190055784ZK.pdf | 2074KB | download |