Compressive sampling of EMG bio-signals

Proceedings - IEEE International Symposium on Circuits and Systems

Volumn , Issue , 2011, Pages 2095-2098

  Salman, Aabeeya ^a   Allstot, Emily G ^a   Chen, Andrew Y ^a   Dixon, Anna M R ^a   Gangopadhyay, Daibashish ^a   Allstot, David J ^a  

^a University of Washington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOSIGNALS; BODY AREA NETWORKS; COMPRESSED SENSING; COMPRESSION FACTOR; COMPRESSIVE SAMPLING; ELECTROCARDIOGRAM SIGNAL; ELECTROMYOGRAM; EMG SIGNAL; FREQUENCY DOMAINS; GAUSSIANS; MEASUREMENT MATRIX; PRE-PROCESSING; RANDOM COEFFICIENTS; RANDOM VALUES; SIGNAL-TO-QUANTIZATION-NOISE RATIO; SPARSE SIGNALS; TIME DOMAIN;

ENERGY UTILIZATION; SIGNAL PROCESSING;

TIME DOMAIN ANALYSIS;

EID: 79960874424     PISSN: 02714310     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISCAS.2011.5938011     Document Type: Conference Paper

References (9)

1. E. Jovanov, et al., "A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation," J. of NeuroEngineering and Rehabilitation, vol. 2, pp. 1-10, March 2005.
2. E. Candès, et al., "An introduction to compressive sampling," IEEE Signal Proc. Mag., vol. 25, pp. 21-30, March 2008.
3. E.G. Allstot, et al., "Compressive sampling of ECG bio-signals: Quantization noise and sparsity considerations," IEEE Biomedical Circuits and Systems Conf., Nov. 2010, pp. 41-44.
4. A. Goldberger, et al., "Physiobank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiological signals," Circulation, vol. 101, no. 23, 2000, pp. 1-6.
5. J.V. Basmajian, et al. Muscles Alive, Their Functions revealed by Electromyography, Fifth Edition. Baltimore, MD: Williams & Wilkins, 1985, pp. 65-101.
6. M.B.I. Reaz, et al., "Techniques of EMG signal analysis: Detection, processing, classification and applications," Biological Proceedings Online, vol. 8, pp. 11-35, Jan. 2006.
7. E. Candès, et al., "Stable signal recovery from incomplete and inaccurate measurements," Communications on Pure and Applied Mathematics, vol. 59, pp. 1207-1233, Aug. 2006.
8. R. Berinde, et al., "Practical near-optimal sparse recovery in the L1 norm," Allerton Conf. on Communication, Control, and Computing, 2008, pp. 198-205.
9. J.A. Tropp, et al., "Computational methods for sparse solution of linear inverse problems," Proc. of the IEEE, vol. 98, pp. 948-958, June 2010.