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

Quality control in nerve conduction studies with coupled knowledge-based system approach.

Y Xiang1, A Eisen, M MacNeil

  • 1Department of Electrical Engineering, University of British Columbia, Vancouver, Canada.

Muscle & Nerve
|February 1, 1992
PubMed
Summary
This summary is machine-generated.

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

Search for Inelastic Dark Matter in Events with Two Displaced Muons and Missing Transverse Momentum in Proton-Proton Collisions at sqrt[s]=13  TeV.

Physical review letters·2024
Same author

Evidence for the Higgs Boson Decay to a Z Boson and a Photon at the LHC.

Physical review letters·2024
Same author

Mitochondrial reverse electron transport in myeloid cells perpetuates neuroinflammation.

bioRxiv : the preprint server for biology·2024
Same author

Probing Small Bjorken-x Nuclear Gluonic Structure via Coherent J/ψ Photoproduction in Ultraperipheral Pb-Pb Collisions at sqrt[s_{NN}]=5.02  TeV.

Physical review letters·2024
Same author

[Construction of a prognostic nomogram combining PET/CT metabolic parameters and blood inflammatory markers for non-small cell lung cancer treated with first-line chemotherapy].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University·2024
Same author

[Prognostic comparison of active surveillance and adjuvant chemotherapy in the treatment of patients with stage Ⅰ ovarian immature teratoma after fertility-sparing surgery].

Zhonghua fu chan ke za zhi·2023
Same journal

Join AANEM.

Muscle & nerve·2026
Same journal

Targeted Muscle Reinnervation for Management and Prevention of Symptomatic Neuroma.

Muscle & nerve·2026
Same journal

AANEM News & Insights.

Muscle & nerve·2026
Same journal

Fat-Fraction Quantification Using Three-Point Dixon Technique in Duchenne Muscular Dystrophy and Its Correlation With Clinical Progression and Genotypic Characteristics: A Single Centre One-Year Prospective Study.

Muscle & nerve·2026
Same journal

Characterizing Combined Central and Peripheral Demyelination-Insights From a Multimodal Comparison With Chronic Inflammatory Demyelinating Polyneuropathy and Multiple Sclerosis.

Muscle & nerve·2026
Same journal

Electrical Modalities in the Rehabilitation of Peripheral Nerve Injuries: State of the Literature and Current Clinical Applications.

Muscle & nerve·2026
See all related articles

Artificial intelligence, through the QUALICON system, can accurately detect technical errors in nerve conduction studies. This AI tool matches professional performance in identifying issues with electrode placement and stimulus settings.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Medical Technology

Background:

  • Nerve conduction studies (NCS) utilize computerized equipment to measure nerve and muscle action potentials.
  • Abnormalities in NCS can stem from technical errors or underlying diseases.
  • Accurate quality control in electromyography (EMG) necessitates identifying technical errors.

Purpose of the Study:

  • To develop and evaluate an artificial intelligence system, QUALICON, for assessing the quality of NCS.
  • To identify and classify technical errors in routine NCS data.

Main Methods:

  • Developed QUALICON, a coupled knowledge-based prototype system.
  • QUALICON extracts numerical features from Compound Muscle Action Potentials (CMAPs) or Sensory Nerve Action Potentials (SNAPs).

Related Experiment Videos

  • A Bayesian network, driven by symbolic data and high-level knowledge, infers electrode placement, polarity, and stimulus strength quality.

    • Main Results:

    • QUALICON successfully infers the quality of stimulating and recording electrode placement.
    • The system identifies potential technical errors such as incorrect polarity or stimulus strength.
    • Preliminary assessments indicate QUALICON performs comparably to expert manual evaluation.

    Conclusions:

    • AI-driven systems like QUALICON can effectively assess the technical quality of NCS.
    • QUALICON offers a promising tool for quality control in electromyography.
    • Automated assessment of NCS technical parameters can enhance diagnostic accuracy and efficiency.