Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Signal processing in evoked potential research: applications of filtering and pattern recognition

C D McGillem, J I Aunon, D G Childers

    Critical Reviews in Bioengineering
    |January 1, 1981
    PubMed
    Summary

    This review covers digital filtering and pattern recognition for improving evoked potential (EP) research. Advanced methods enhance signal clarity, crucial for analyzing low signal-to-noise ratio data in neuroscience.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Constrained optimization of image restoration filters.

    Applied optics·2010
    Same author

    Nonlinear system identification and overparameterization effects in multisensory evoked potential studies.

    IEEE transactions on bio-medical engineering·2000
    Same author

    Labelling and discrimination of a synthetic fricative continuum in noise: a study of absolute duration and relative onset time cues.

    Journal of speech and hearing research·1996
    Same author

    Modeling the glottal volume-velocity waveform for three voice types.

    The Journal of the Acoustical Society of America·1995
    Same author

    Speech synthesis by glottal excited linear prediction.

    The Journal of the Acoustical Society of America·1994
    Same author

    Measuring and modeling vocal source-tract interaction.

    IEEE transactions on bio-medical engineering·1994

    Area of Science:

    • Neuroscience
    • Signal Processing
    • Biomedical Engineering

    Background:

    • Evoked potential (EP) research often faces low signal-to-noise ratios, necessitating advanced signal processing techniques.
    • Historically, analog filtering was used, but digital filtering has become predominant with advances in computing power.

    Purpose of the Study:

    • To review waveform estimation via filtering and information extraction via pattern recognition in evoked potential research.
    • To discuss the evolution from analog to digital filtering methods.
    • To explore the application of statistical pattern recognition techniques to EP data.

    Main Methods:

    • Review of various digital filtering techniques, including Wiener filtering (single and multiple channel), Kalman filtering, minimum mean square error filtering, maximum signal-to-noise filtering, and nonlinear filters.

    Related Experiment Videos

  • Discussion of adaptive filtering techniques.
  • Overview of pattern recognition methods based on statistical decision theory, including linear stepwise discriminant analysis and linear/quadratic discriminant functions.

    • Main Results:

    • Digital filtering offers significant improvements in waveform estimation for evoked potentials compared to analog methods.
    • Pattern recognition techniques, grounded in statistical decision theory, are increasingly applied for information extraction from EP data.
    • Specific applications in psychophysiological testing, particularly for auditory and visual event-related potentials, are highlighted.

    Conclusions:

    • Digital filtering and pattern recognition are essential tools for advancing evoked potential research.
    • The integration of these advanced signal processing techniques is crucial for accurate analysis and interpretation of neural signals.
    • Future research can benefit from continued development and application of these methods in neuroscience.