Evidence map›Paper›PMID 31366940›Full record

ArticleScientific reports2019

Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings.

Ryan G L Koh, Adrian I Nachman, José Zariffa

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
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  3. Article
  4. Review
  5. Article
  6. Article
  7. Machine Learning in Pain Neuromodulation.Advances in experimental medicine and biology · 2024
    Review
  8. Article
  9. Machine Learning in Spinal Cord Stimulation for Chronic Pain.Operative neurosurgery (Hagerstown, Md.) · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Calcium imaging for analgesic drug discovery.Neurobiology of pain (Cambridge, Mass.)
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Ryan G L KohInstitute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G4, Canada.ORCID http://orcid.org/0000-0001-8662-1008
Adrian I NachmanInstitute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G4, Canada.
José ZariffaInstitute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G4, Canada. jose.zariffa@utoronto.ca.ORCID http://orcid.org/0000-0002-8842-745X
University of Toronto · CAUniversity Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral neural signals have the potential to provide the necessary motor, sensory or autonomic information for robust control in many neuroprosthetic and neuromodulation applications. However, developing methods to recover information encoded in these signals is a significant challenge. We introduce the idea of using spatiotemporal signatures extracted from multi-contact nerve cuff electrode recordings to classify naturally evoked compound action potentials (CAP). 9 Long-Evan rats were implanted with a 56-channel nerve cuff on the sciatic nerve. Afferent activity was selectively evoked in the different fascicles of the sciatic nerve (tibial, peroneal, sural) using mechano-sensory stimuli. Spatiotemporal signatures of recorded CAPs were used to train three different classifiers. Performance was measured based on the classification accuracy, F

Indexed as

Action PotentialsAnimalsElectrodesEvoked PotentialsNeural ConductionNeural PathwaysPeripheral Nervous SystemRatsRats, Long-EvansSciatic Nerve

Identifiers

PMID31366940
PMCPMC6668407
OpenAlexW2965316760

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.