Adaptive least squares support vector machines filter for hand tremor canceling in microsurgery
作者： Zhi Liu , Qihang Wu , Yun Zhang , CL Philip Chen , None
DOI: 10.1007/S13042-011-0012-5
关键词:
摘要: One of the main problems for effective control a minimally invasive surgery (MIS) is imprecision that caused by hand tremor. In this paper, novel adaptive filter, least squares support vector machines filter (LS-SVMAF), proposed to overcome problem. Compared with traditional methods like multi layer perceptron (MLP), LS-SVM shows superior performance nonlinear modeling small scale data set or high dimensional input space. With LS-SVMAF, we can model and predict tremor more effectively improve precision reliability in master–slave robotic system microsurgery. Simulation results demonstrate effectiveness its over competing rivals.
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Ming-guang Zhang, Xing-gui Wang, Wen-hui Li, Nonlinear System Identification using Least Squares Support Vector Machines international conference on neural networks and brain. ,vol. 1, pp. 414- 418 ,(2005) , 10.1109/ICNNB.2005.1614645
Nello Cristianini, John Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-based Learning Methods ,(2000)
Riley Po, Rosen Mj, Evaluating manual control devices for those with tremor disability. Journal of Rehabilitation Research and Development. ,vol. 24, pp. 99- 110 ,(1987)
Cheng-Jian Lin, Shang-Jin Hong, Chi-Yung Lee, None, Using Least Squares Support Vector Machines for Adaptive Communication Channel Equalization International Journal of Applied Science and Engineering. ,vol. 3, pp. 51- 59 ,(2005) , 10.6703/IJASE.2005.3(1).51
S. Iplikci, Support vector machines based neuro-fuzzy control of nonlinear systems Neurocomputing. ,vol. 73, pp. 2097- 2107 ,(2010) , 10.1016/J.NEUCOM.2010.02.008
Chin-Teng Lin, Chia-Feng Juang, An adaptive neural fuzzy filter and its applications systems man and cybernetics. ,vol. 27, pp. 635- 656 ,(1997) , 10.1109/3477.604107
J.A.K. Suykens, J. Vandewalle, B. De Moor, Optimal control by least squares support vector machines Neural Networks. ,vol. 14, pp. 23- 35 ,(2001) , 10.1016/S0893-6080(00)00077-0
Qinjun Du, Xueyi Zhang, Kinematics Analysis and Motion Control of Radio Frequency Ablation Surgical Robot international conference on control and automation. pp. 1890- 1895 ,(2007) , 10.1109/ICCA.2007.4376690
Glenn Fung, Olvi L. Mangasarian, Proximal support vector machine classifiers knowledge discovery and data mining. pp. 77- 86 ,(2001) , 10.1145/502512.502527
R.H. Taylor, D. Stoianovici, Medical robotics in computer-integrated surgery international conference on robotics and automation. ,vol. 19, pp. 765- 781 ,(2003) , 10.1109/TRA.2003.817058