Promise of embedded system with GPU in artificial leg control: Enabling time-frequency feature extraction from electromyography

Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Volumn , Issue , 2009, Pages 6926-6929

  Xiao, Weijun ^a   Huang, He ^a   Sun, Yan ^a   Yang, Qing ^a  

^a and Biomedical Engineering ^*  (United States)

Author keywords

Control of artificial limbs; Electromyography; Embedded system; High performance computing

Indexed keywords

ARTIFICIAL LIMBS; BIOMEDICAL SIGNAL PROCESSING; ELECTROMYOGRAPHY; EXTRACTION; FEATURE EXTRACTION; GRAPHICS PROCESSING UNIT; MEDICAL APPLICATIONS; PATTERN RECOGNITION; REAL TIME SYSTEMS; SIGNAL ANALYSIS;

COMPUTATIONAL SPEED; ELECTROMYOGRAPHIC SIGNAL; GRAPHIC PROCESSOR UNITS; HIGH PERFORMANCE COMPUTING; NONSTATIONARY SIGNALS; REAL TIME COMPUTING; REAL-TIME COMPUTATIONS; TIME FREQUENCY FEATURES;

EMBEDDED SYSTEMS;

EID: 77950985314     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2009.5333633     Document Type: Conference Paper

References (22)

1. J. Basmajian and C. De Luca, "Muscles alive: their functions revealed by electromyography," 5 ed. Baltimore, MD: Williams and Wilkins, 1985.
2. S. H. Park and S. P. Lee, "EMG pattern recognition based on artificial intelligence techniques," IEEE Transactions on Rehabilitation Engineering, vol.6, pp. 400-405, 1998.
3. K. Englehart, B. Hudgins, P. A. Parker, and M. Stevenson, "Classification of the myoelectric signal using time-frequency based representations," Medical Engineering& Physics, vol.21, pp. 431-438, 1999.
4. K. Englehart, B. Hudgins, and P. A. Parker, "A wavelet-based continuous classification scheme for multifunction myoelectric control," IEEE Transactions on Biomedical Engineering, vol.48, pp. 302-311, 2001.
5. K. Englehart and B. Hudgins, "A robust, real-time control scheme for multifunction myoelectric control," IEEE Transactions on Biomedical Engineering, vol.50, pp. 848-854, 2003.
6. D. Graupe, A. A. Beex, W. J. Monlux, and I. Magnussen, "A multifunctional prosthesis control system based on time series identification of EMG signals using microprocessors," Bulletin of Prosthetics Research, vol.10, pp. 4-16, 1977.
7. H. Huang, P. Zhou, G. Li, and T. A. Kuiken, "An analysis of EMG electrode configuration for targeted muscle reinnervation based neural machine interface," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.16, pp. 37-45, 2008.
8. H. Huang, T. Kuiken, and R. D. Lipschutz, "A strategy for identifying locomotion modes using surface electromyography," IEEE Transactions on Biomedical Engineering, vol.56, pp. 65-73, 2009.
9. B. Hudgins, P. Parker, and R. Scott, "A new strategy for multifunction myoelectric control," in IEEE Transactions on Biomedical Engineering, vol.40, 1993, pp. 82-94.
10. L. Cohen, Time-frequency analysis. Englewood Cliffs, N.J: Prentice Hall PTR, 1995.
11. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern classification, 2nd ed. New York: Wiley, 2001.
12. I. Otto Bock Orthopedic Industry, Manual for the 3c100 Otto Bock CLEG. Duderstadt, Germany, 1998.
13. OSSUR, RHEO KNEE: http://bionics.ossur.com/Products/RHEOKNEE/ ACT.
14. "GPGPU.org," http://www.gpgpu.org.
15. NVIDIA Corporation, "CUDA: compute unified device architecture programming guide," http://www.nividia.com.
16. N. Fujimoto, "Faster matrix-vector multiplication on GeForce 8800 GTX," In the Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2008.
17. V. Volkov and J. W. Demmel, "Benchmarking GPUs to tune dense linear algebra," In the Proceedings of the 2008 ACM/IEEE Conference on Supercomputing, Austin, TX, USA, 2008.
18. S. Kak, "The discrete finite Hilbert transform," Indian Journal of Pure and Applied Mathematics, vol.8, pp. 1385-1390, 1977.
19. V. Bernasconi, L. Bollea, A. Breda, P. Daponte, G. Maroncelli, and S. Rapuano, " A TFR-based method for the quality assessment of UMTS signals: an application on the first Italian experimental network," IEEE Transactions on Instrumentation and Measurement, vol.53, pp. 485-492, 2004.
20. S. Wold, K. Esbensen, and P. Geladi, "Principal component analysis," Chemometrics and Intelligent Laboratory Systems, vol.2, pp. 37-52.
21. "NVIDIA Corporation. CUDA: CUFFT library," http://developer. download.nvidia.com/compute/cuda/2-1/toolkit/docs/CUFFT-Librar y-2.1.pdf, 2008.
22. M. Frigo and S. G. Johnson, "The design and implementation of FFTW3," in IEEE Proceedings of the Special Issue on Program Generation, Optimization, and Platform Adaptation, vol.93, pp. 216-231, 2005.