« Previous
Next »
Artificial Intelligence in Medicine
Volume 37, Issue 1
, Pages 55-64
, May 2006
A novel method for automated EMG decomposition and MUAP classification
References
- . Towards understanding the EMG signal. 4th ed.. Baltimore: Williams & Wilkinson; 1978;
- . Pitfalls in electrodiagnosis. J Neurophysiol. 1999;81:1115–1126
- . Optimal resolution of superimposed action potentials. IEEE Trans Biomed Eng. 2002;49:640–650
- . Review of quantitative and automated needle electromyographic analyses. IEEE Trans Biomed Eng. 1981;506–514
- . A new framework and computer program for quantitative EMG signal analysis. IEEE Trans Biomed Eng. 1984;31:857–863
- . New signal processing techniques for the decomposition of EMG signals. Med Biol Eng Comput. 1992;30:591–599
- . Multimotor action potential analysis (MMA). Muscle Nerve. 1995;18:1155–1166
- . Quantitative analysis of individual motor unit potentials: a proposition for standardized technology and criteria for measurement. J Clin Neurophysiol. 1986;3:313–348
- . Action potential parameters in normal human muscle and their dependence on physical variables. Acta Physiol Scand. 1954;32:200–215
- . An introduction to electromyography. Copenhagen: Gyldendal; 1957;
- . A procedure for decomposing the myoelectric signal into its constituent action potentials: part I, execution and test for accuracy. Technique, theory and implementation. IEEE Trans Biomed Eng. 1982;29:149–157
- . Multi-MUP EMG analysis—a two year experience in daily clinical work. Electroencephalography and clinical neurophysiol. Amsterdam, The Netherlands: Elsevier Science; 1995;pp. 145–154
- . Methods for computer aided measurement of motor unit parameters. In: Ellington RJ, et al. editor. Proceedings of the London Symp., EEG suppl. 13–20. 1987;
- . Automatic decomposition of selective needle detected myoelectric signals. IEEE Trans Biomed Eng. 1988;35:1–10
- . NNERVE: neural network extraction of repetitive vectors for electromyography—part II: algorithm. IEEE Trans Biomed Eng. 1994;41:1053–1061
- . Automatic decomposition of the clinical electromyogram. IEEE Trans Biomed Eng. 1985;32:470–476
- . Decomposition of multiunit electromyographic signals. IEEE Trans Biomed Eng. 1999;46:685–697
- . Extraction of MUAP from NEMG signal using self-organization competing NN. Hefei 230026: Dept. of Electronic Science & Tech., Univ. of Science & Tech. of China; 2001;
- . Automatic identification of motor unit action potential trains from electromyographic signals using fuzzy techniques. Med Biol Eng Comput. 2003;41:646–653
- . A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients. IEEE Trans Biomed Eng. 2003;50:58–69
- . Unsupervised Pattern Recognition for the Classification of EMG Signals. IEEE Trans Biomed Eng. 1999;46:169–178
- . On finding the number of clusters. Patt Rec Lett. 1999;20:405–416
- . Decomposition quantitative analysis of clinical electromyographic signals. Med Eng Phys. 1999;21:389–404
- . Robust supervised classification of motor unit action potentials. Med Biol Eng Comput. 1998;36:75–82
- . Multi-motor unit action potential analysis (MMA). Muscle Nerve. 1995;18:1155–1166
- . 2nd ed.. Myology. vol. 1. United States: McGraw-Hill Inc.; 1994;
- . A training algorithm for optimal margin classifiers. In: Proceedings of Fifth Annual Workshop on Computational Learning Theory. Pittsburgh, PA, United States. ACM Press; 1992;
- . Support-vector network. Machine Learn. 1995;32:273–297
- Chang C, Lin CJ. LIBSVM, a library for support vector machines. Available: http://www.csie.ntu.edu.tw/∼cjlin/libsvm [Online]; 2004 [accessed: 8 September].
- . Single layer learning revisited: a stepwise procedure for building and training a neural network. In: Fogelman F, Hérault J editor. Proceedings of NATO workshop Les Arcs 1989. Springer; 1989;
- . A comparison of methods for multi-class support vector machines. IEEE Trans Neural Networks. 2002;13:415–425
- Chang CC, Lin CJ. LIBSVM: introduction and benchmarks. Available: http://www.csie.ntu.edu.tw/∼cjlin/libsvm [Online]; 2004 [Accessed: 8 September].
- Platt J. Sequential minimal optimization: a fast algorithm for training support vector machines. Microsoft Research. Technical Report MSR-TR-98-14. Washington, United States: Redmond; 1998.
- Keerthi SS, Shevade SK, Bhattacharyya C, Murthy KR. Improvements to Platt's SMO algorithm for SVM classifier design. Indian Institute of Science, Dept. of Computer Science and Automation. Technical Report. Bangalore, India; 1999.
PII: S0933-3657(05)00106-5
doi: 10.1016/j.artmed.2005.09.002
© 2005 Elsevier B.V. All rights reserved.
« Previous
Next »
Artificial Intelligence in Medicine
Volume 37, Issue 1
, Pages 55-64
, May 2006
