High-Resolution Alignment of Sampled Waveforms

IEEE Transactions on Biomedical Engineering

Volumn BME-31, Issue 6, 1984, Pages 462-468

  Mcgill, Kevin C ^a,b   Dorfman, Leslie J ^a,b  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b VA PALO ALTO HEALTH CARE SYSTEM   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL ENGINEERING - ELECTROMYOGRAPHY; COMPUTER PROGRAMMING - ALGORITHMS; WAVEFORM ANALYSIS - COMPUTER AIDED ANALYSIS;

MOTOR UNIT ACTION POTENTIALS; NYQUIST RATE;

ELECTRIC WAVEFORMS;

ALGORITHM; METHODOLOGY; NONHUMAN; RESOLUTION; SIGNAL PROCESSING; THEORETICAL STUDY; WAVEFORM;

EID: 0021286283     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.1984.325413     Document Type: Article

References (17)

1. C. W. Helstrom, Statistical Theory of Signal Detection. New York: McGraw-Hill, 1965.
2. M. Abeles and M. H. Goldstein, “Multispike train analysis,” Proc. IEEE, vol. 65, pp. 762–773, 1975.
3. J. Bergmans, “Computer-assisted measurement of the parameters of single motor unit potentials in human electromyography,” in New Developments in Electromyography and Clinical Neurophysiology, vol. 2, J.E. Desmedt, Ed. Basel, Switzerland: Kerger, 1973, pp. 482–488.
4. V. J. Prochazka and H. H. Kornhuber, “On-line multi-unit sorting with resolution of superposition potentials,” Electroenceph. Clin, Neurophysiol., vol. 34, pp. 91–93, 1973.
5. B. C. Wheeler and W. J. Heetderks, “The effects of sampling rate on the signal-to-noise ratios of biological signals,” in Proc. 8th New England Bioeng. Conf., 1980, pp. 446–450.
6. —, “A comparison of techniques for classification of multiple neural signals,” IEEE Trans. Biomed. Eng., vol. BME-29,pp. 752–759, 1982.
7. R. S. LeFever and C. J. De Luca, “A procedure for decomposing the myoelectric signal into its constituent action potentials–Part I: Technique, theory, and implementation,” IEEE Trans. Biomed. Eng.,vol. BME-29,pp. 144–157, 1982.
8. A. Papoulis, Signal Analysis. New York: McGraw-Hill, 1977.
9. S. Usui and I. Amidror, “Digital low-pass differentiation for biological signal processing,” IEEE Trans. Biomed. Eng., vol. BME-29, pp. 686–693, 1982.
10. K. C. McGill, K. L. Cummins, and L. J. Dorfman, “Automatic decomposition of the clinical electromyogram,” in preparation.
11. A. V. Oppenheim and R. W. Schafer, Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1975.
12. P. E. Gill, W. Murray, and M. H. Wright, Practical Optimization. New York: Academic, 1981.
13. K. C. McGill, “A method for quantitating the clinical electromyogram,” Ph.D. dissertation, Stanford Univ., Stanford, CA, 1984.
14. R. J. Marks, II, and M. W. Hall, “Differintegral interpolation from a band-limited signal’s samples,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-29, pp. 872–877, 1981.
15. C. L. Lawson and R. J. Hanson, Solving Least Squares Problems. Englewood Cliffs, NJ: Prentice-Hall, 1974.
16. R.J.P. De Figueiredo and A. Gerber, “Separation of superimposed signals by a cross-correlation method,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-31, pp. 1084–1089, 1983.
17. J. C. Hansen, “Separation of overlapped waveforms having known temporal distributions,” J. Neurosci. Meth., vol. 9, pp. 127–139, 1983.