Nonlinear modeling using support vector machine for heart rate response to exercise

[1]  B. Saltin,et al.  CARDIAC OUTPUT DURING SUBMAXIMAL AND MAXIMAL WORK. , 1964, Journal of applied physiology.

[2]  L N KATZ,et al.  Effect of training on response of cardiac output to muscular exercise in athletes. , 1955, Journal of applied physiology.

[3]  Johan A. K. Suykens,et al.  Identification of MIMO Hammerstein models using least squares support vector machines , 2005, Autom..

[4]  Rory A. Cooper,et al.  Model reference adaptive control of heart rate during wheelchair ergometry , 1998, IEEE Trans. Control. Syst. Technol..

[5]  Alexander J. Smola,et al.  Support Vector Regression Machines , 1996, NIPS.

[6]  P. Paré,et al.  Prediction of heart rate and oxygen uptake during incremental and maximal exercise in healthy adults. , 1994, Chest.

[7]  Yi Zhang,et al.  Machine learning-based nonlinear model predictive control for heart rate response to exercise , 2012 .

[8]  V. Vapnik.  Pattern recognition using generalized portrait method , 1963 .

[9]  A.V. Savkin,et al.  Estimation of Walking Energy Expenditure by Using Support Vector Regression , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[10]  Alexander J. Smola,et al.  Learning with kernels , 1998 .

[11]  Andrey V. Savkin,et al.  Nonlinear Modeling and Control of Human Heart Rate Response During Exercise With Various Work Load Intensities , 2008, IEEE Transactions on Biomedical Engineering.

[12]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machines , 2002 .

[13]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[14]  Miloslav Hájek,et al.  Mathematical model of heart rate regulation during exercise , 1980, Autom..

[15]  Y L Chen,et al.  Effect of combined dynamic and static workload on heart rate recovery cost. , 1998, Ergonomics.