• DocumentCode
    1213695
  • Title

    High-Resolution Alignment of Sampled Waveforms

  • Author

    McGill, Kevin C. ; Dorfman, Leslie J.

  • Author_Institution
    Department of Neurology, Stanford University School of Medicine, Stanford, CA 94305, and the Rehabilitative Research and Development Center, Palo Alto Veterans Administration Medical Center
  • Issue
    6
  • fYear
    1984
  • fDate
    6/1/1984 12:00:00 AM
  • Firstpage
    462
  • Lastpage
    468
  • Abstract
    Waveforms are often sampled faster than the Nyquist rate to obtain desired temporal resolution, even though, theoretically, oversampling adds no information and should not be necessary. This paper shows how high resolution can be achieved efficiently from data sampled at the Nyquist rate by working with coefficients of the Fourier-series expansion of the continuous interpolating waveform. Practical algorithms are presented for aligning and comparing waveforms, locating peaks, resolving superimpositions, and averaging overlapping waveforms. The algorithms prove to be more accurate, and to require fewer computations and less storage than techniques which employ continuous oversampling in many signal-processing applications, particularly template matching.
  • Keywords
    Computational efficiency; Digital filters; Electromyography; Low-frequency noise; Noise level; Noise reduction; Sampling methods; Signal resolution; Signal to noise ratio; Thumb; Electromyography; Humans; Information Theory; Motor Neurons;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.1984.325413
  • Filename
    4121865