Single Site Electromyograph Amplitude Estimation

IEEE Transactions on Biomedical Engineering

Volumn 41, Issue 2, 1994, Pages 159-167

  Clancy, Edward A ^a,b   Hogan, Neville ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b Liberty Mutual Research Institute   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL FILTERING; ELECTROMYOGRAPHY; MATHEMATICAL MODEL; REVIEW; SIGNAL NOISE RATIO; TORQUE; WAVEFORM;

ADULT; BIOMECHANICS; CALIBRATION; ELBOW; ELECTROMYOGRAPHY; FEMALE; FOURIER ANALYSIS; HUMAN; ISOMETRIC CONTRACTION; MALE; MODELS, BIOLOGICAL; MODELS, STATISTICAL; REFERENCE VALUES; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUPPORT, U.S. GOV'T, NON-P.H.S.; SUPPORT, U.S. GOV'T, P.H.S.;

EID: 0028356239     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/10.284927     Document Type: Article

References (15)

1. E. Kaiser and I. Petersen, “Adaptive filter for EMG control signals.” in The Control of Upper-Extremity Prostheses and Orthoses. Springfield, IL: Charles C. Thomas, 1974, pp. 54–57.
2. N. Hogan and R. W. Mann, “Myoelectric signal processing: Optimal estimation applied to electromyography—Part I: Derivation of the optimal myoprocessor,” IEEE Trans. Biomed. Eng., vol. 27, pp. 382–395, 1980.
3. — “Myoelectric signal processing: Optimal estimation applied to electromyography—Part II: Experimental demonstration of optimal myoprocessor performance,” IEEE Trans. Biomed. Eng., vol. 27, pp. 396–410, 1980.
4. M. I. A. Harba and P. A. Lynn, “Optimizing the acquisition and processing of surface electromyographic signals,” J. Biomed. Eng., vol. 3, pp. 100–106, 1981.
5. T. D’Alessio, “Some results on the optimization of a digital processor for surface EMG signals,” Electromyogr. Clin. Neurophysiol., vol. 24, pp. 625–643, 1984.
6. G. C. Filligoi and P. Mandarini, “Some theoretic results on a digital EMG signal processor,” IEEE Trans. Biomed. Eng., vol. 31, pp. 333–341, 1984.
7. H. Roesler, “Statistical analysis and evaluation of myoelectric signals for proportional control,” in The Control of Upper-Extremity Prostheses and Orthoses. Springfield, IL, Charles C. Thomas, 1974, pp. 44–53.
8. P. A. Parker, J. A. Siulier, and R. N. Scott, “Signal processing for the multistate myoelectric channel,” Proc. IEEE, vol. 65, pp. 662–674, 1977.
9. E. Kwatny, D. H. Thomas, and H. G. Kwatny, “An application of signal processing techniques to the study of myoelectric signals,” IEEE Trans. Biomed. Eng., vol. 17, pp. 303–313, 1970.
10. E. A. Clancy, “Stochastic modeling of the relationship between the surface electromyogram and muscle torque,” Ph.D. dissertation. Dept. Elect. Eng. Comp. Sci., M.I.T., Cambridge, MA, Jan. 11, 1991.
11. S. J. Greelish, “Five new amplifiers for detecting myo- and bioelectric signals,” in Proc. 10th Annual Conf. Rehab. Tech.—RESNA ’87. San Jose, CA, June 19–23, 1987, pp. 190–192.
12. E. A. Muller, “Physiological methods of increasing human physical work capacity,” Ergonomics, vol. 8, pp. 409–424, 1965.
13. W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing. New York: Cambridge Univ. Press, 1988.
14. G. C. Joyce and P. M. H. Rack, “The effects of load and force on tremor at the normal human elbow joint,” J. Physiol., vol. 240, pp. 375–396, 1974.
15. R. J. Triolo, D. H. Nash, and G. D. Moskowitz, “The identification of time series models of lower extremity EMG for the control of prostheses using Box-Jenkins criteria,” IEEE Trans. Biomed. Eng., vol. 35, pp. 584–594, 1988.