Support vector machine for classification of walking conditions of persons after stroke with dropped foot.
暂无分享,去创建一个
[1] Marimuthu Palaniswami,et al. Support vector machines for automated gait classification , 2005, IEEE Transactions on Biomedical Engineering.
[2] T Chau,et al. A review of analytical techniques for gait data. Part 2: neural network and wavelet methods. , 2001, Gait & posture.
[3] Merryn J Mathie,et al. Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement , 2004, Physiological measurement.
[4] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[5] K. Y. Tong,et al. Command control for functional electrical stimulation hand grasp systems using miniature accelerometers and gyroscopes , 2003, Medical and Biological Engineering and Computing.
[6] Bernhard Schölkopf,et al. Comparing support vector machines with Gaussian kernels to radial basis function classifiers , 1997, IEEE Trans. Signal Process..
[7] Eric Watelain,et al. Identification and classification of toe-walkers based on ankle kinematics, using a data-mining method. , 2006, Gait & posture.
[8] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[9] Kim L Coleman,et al. Accelerometer monitoring of home- and community-based ambulatory activity after stroke. , 2004, Archives of physical medicine and rehabilitation.
[10] Pascal Fua,et al. Estimation and visualization of sagittal kinematics of lower limbs orientation using body-fixed sensors , 2006, IEEE Transactions on Biomedical Engineering.
[11] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[12] Hongyin Lau,et al. The reliability of using accelerometer and gyroscope for gait event identification on persons with dropped foot. , 2008, Gait & posture.
[13] Kamiar Aminian,et al. Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly , 2002, IEEE Transactions on Biomedical Engineering.
[14] M.R. Popovic,et al. A reliable gait phase detection system , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[15] Jürgen Perl,et al. A neural network approach to movement pattern analysis. , 2004, Human movement science.
[16] Angelo M. Sabatini,et al. Assessment of walking features from foot inertial sensing , 2005, IEEE Transactions on Biomedical Engineering.
[17] Kamiar Aminian,et al. Stair climbing detection during daily physical activity using a miniature gyroscope. , 2005, Gait & posture.
[18] Joarder Kamruzzaman,et al. Support Vector Machines and Other Pattern Recognition Approaches to the Diagnosis of Cerebral Palsy Gait , 2006, IEEE Transactions on Biomedical Engineering.
[19] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[20] J. Perry,et al. Gait Analysis , 2024 .
[21] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[22] B. Auvinet,et al. Reference data for normal subjects obtained with an accelerometric device. , 2002, Gait & posture.
[23] M. Murphy,et al. Training effects of short bouts of stair climbing on cardiorespiratory fitness, blood lipids, and homocysteine in sedentary young women , 2005, British Journal of Sports Medicine.
[24] Brian D. Ripley,et al. Neural Networks and Related Methods for Classification , 1994 .
[25] R Begg,et al. A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data. , 2005, Journal of biomechanics.
[26] T Chau,et al. A review of analytical techniques for gait data. Part 1: Fuzzy, statistical and fractal methods. , 2001, Gait & posture.
[27] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.
[28] Jooyoung Park,et al. Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.
[29] M H Granat,et al. A practical gait analysis system using gyroscopes. , 1999, Medical engineering & physics.
[30] Hailong Zhu,et al. Support vector machine for classification of walking conditions using miniature kinematic sensors , 2008, Medical & Biological Engineering & Computing.
[31] J. Kamruzzaman,et al. Neural networks for detection and classification of walking pattern changes due to ageing , 2006, Australasian Physics & Engineering Sciences in Medicine.