• IEEE Trans Biomed Eng · Mar 1992

    Separation of action potentials in multiunit intrafascicular recordings.

    • E V Goodall and K W Horch.
    • Department of Bioengineering, University of Utah, Salt Lake City 84112.
    • IEEE Trans Biomed Eng. 1992 Mar 1; 39 (3): 289-95.

    AbstractClassification of action potentials in multiunit recordings was based on the use of various types of features to uniquely characterize action potentials from different cells. We compared classification results obtained using three types of descriptive features: digitized data points, amplitude and duration (time domain) parameters, and fast Fourier transform (FFT) coefficients. Digitized data points used as descriptive features provided good classification success and required minimal computation. Time-domain features gave comparable results but required more computation. FFT coefficients were less effective than the other features. As the signal-to-noise ratio of the recordings increased, smaller differences in feature values could be discriminated.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.