Evidence map›Paper›PMID 40345081›Full record

ArticleNeurophysiologie clinique = Clinical neurophysiology2025

Characterizing repeater F waves using the compound muscle action potential scan and machine learning techniques.

Xiaoyan Li, Maoqi Chen, Paul E Barkhaus, Sanjeev D Nandedkar, Marek Cierny, Caitlin Moore, Ping Zhou

Abstract read
In one paragraph

Article in Neurophysiologie clinique = Clinical neurophysiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xiaoyan LiFischell Department of Bioengineering, University of Maryland at College Park, College Park, MD, USA; Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA. Electronic address: xli025@umd.edu.
Maoqi ChenSchool of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, PR China.
Paul E BarkhausDepartment of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
Sanjeev D NandedkarDepartment of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA; Natus Medical, Inc, Middleton, WI, USA.
Marek CiernyDepartment of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
Caitlin MooreDepartment of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
Ping ZhouSchool of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, PR China.

Funding

High-Density surface EMG based CMAP scan for motor unit number estimationR21NS113716 · NINDS · MEDICAL COLLEGE OF WISCONSIN · PI BARKHAUS, PAUL E, LI, XIAOYAN · 2020 to 2020
$432k
NINDS NIH HHS R21 NS113716
6 · The paper itself

Abstract

objectivesThe purpose of this study is to introduce a new analytical technique on repeater F waves (RFws) using compound muscle action potential (CMAP) scan and new features to differentiate the nerves innervating hand muscles.

methodsTwenty-four healthy subjects participated in the CMAP scan study. Tests were performed on the abductor pollicis brevis (APB) and abductor digit minimi (ADM) muscles. RFws were extracted using unsupervised machine learning and analyzed through conventional characteristics such as amplitude, latency, indices of F repeaters and total F repeaters, as well by new variables, including relative stimulus intensity (ReSI), relative F/M ratio (RF/MR), and range of stimulation intensity (RaSI).

resultsSignificantly higher indices of F repeaters (APB: 18.42±4.92 %, ADM: 13.58±4.68 %, p < 0.005) and total F repeaters (APB: 34.75±7.8 %, ADM: 26.67±8.56 %, p < 0.005) were observed in the APB compared with the ADM muscles. The ReSI (Z = 13.81, p < 0.001) and RaSI (Z=-2.46, p < 0.05) showed significant differences between the two muscles. DISCUSSION AND

conclusionThis study provides normative data for RFws based on the CMAP scan recording and identifies different characteristics of repeaters between APB and ADM muscles. Findings of the study improve understanding of motoneuron physiological properties in hand muscles. The CMAP scan-based F wave analysis can be combined with motor unit number estimation technique to provide insights into surviving motoneuron function in neurological disorders.

Indexed as

Action PotentialsMachine LearningMuscle, SkeletalAdultElectromyographyFemaleHandHumansMaleYoung AdultCompound muscle action potential (CMAP) scanelectrophysiologyhand musclesmachine learningMotoneuron (MN)Repeater F-waves

Identifiers

PMID40345081
PMCPMC13048848

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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.