Aliasing rejection in Precision Decomposition of EMG signals

The use of Artificial Intelligence (AI) methods in Precision Decomposition (PD) of indwelling and surface electromyographic (EMG) signals has led to the recent development of systems that can automatically resolve most instances of complex superposition among action potentials. The remaining errors have to be corrected by a user-interactive editing process. Typically, 25% to 50% of such errors involve action-potential aliasing, whereby the action potential of a motor unit is incorrectly identified in signal data that actually supports the action potential of another motor unit. To drastically reduce this class of errors, we have added a new aliasing-rejection mechanism in PD algorithms. Experimental results on real EMG signals show that aliasing-related errors of the Precision Decomposition technique are thereby reduced by 80% to 90%.

[1]  C.J. De Luca,et al.  Multi-Receiver Precision Decomposition of Intramuscular EMG Signals , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  R. Wotiz,et al.  Improved resolution of pulse superpositions in a knowledge-based system EMG decomposition , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  Joshua C. Kline,et al.  Decomposition of surface EMG signals. , 2006, Journal of neurophysiology.

[4]  S. Hamid Nawab,et al.  A C++ software environment for the development of embedded signal processing systems , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[5]  Ronald S. Lefever,et al.  A Procedure for Decomposing the Myoelectric Signal Into Its Constituent Action Potentials - Part I: Technique, Theory, and Implementation , 1982, IEEE Transactions on Biomedical Engineering.

[6]  Victor R. Lesser,et al.  IPUS: An Architecture for the Integrated Processing and Understanding of Signals , 1995, Artif. Intell..

[7]  C.J. De Luca,et al.  Next-generation decomposition of multi-channel EMG signals , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.