A novel approach to the diagnostic assessment of carpal tunnel syndrome based on the frequency domain of the compound muscle action potential

Basit Öğe Kaydı
dc.authoridAlcan, Veysel/0000-0002-7786-8591
dc.authoridKaya, Hilal/0000-0003-4787-105X
dc.contributor.authorAlcan, Veysel
dc.contributor.authorKaya, Hilal
dc.contributor.authorZinnuroglu, Murat
dc.contributor.authorKaratas, Gulcin Kaymak
dc.contributor.authorCanal, Mehmet Rahmi
dc.date.accessioned2025-03-17T12:25:29Z
dc.date.available2025-03-17T12:25:29Z
dc.date.issued2020
dc.departmentTarsus Üniversitesi
dc.description.abstractConventional electrophysiological (EP) tests may yield ambiguous or false-negative results in some patients with signs and symptoms of carpal tunnel syndrome (CTS). Therefore, researchers tend to investigate new parameters to improve the sensitivity and specificity of EP tests. We aimed to investigate the mean and maximum power of the compound muscle action potential (CMAP) as a novel diagnostic parameter, by evaluating diagnosis and classification performance using the supervised Kohonen self-organizing map (SOM) network models. The CMAPs were analyzed using the fast Fourier transform (FFT). The mean and maximum power parameters were calculated from the power spectrum. A counter-propagation artificial neural network (CPANN), supervised Kohonen network (SKN) and XY-fused network (XYF) were compared to evaluate the classification and diagnostic performance of the parameters using the confusion matrix. The mean and maximum power of the CMAP were significantly lower in patients with CTS than in the normal group (p < 0.05), and the XYF network had the best total performance of classification with 91.4%. This study suggests that the mean and maximum power of the CMAP can be considered as less time-consuming parameters for the diagnosis of CTS without using additional EP tests which can be uncomfortable for the patient due to poor tolerance to electrical stimulation.
dc.description.sponsorshipAnkara Yildirim Beyazit University [BAP 4043]
dc.description.sponsorshipThe authors thank the members of the Department of Physical Medicine and Rehabilitation, School of Medicine, Gazi University for collecting data. Moreover, we thank Ankara Yildirim Beyazit University for supporting this study with the project number BAP 4043.
dc.identifier.doi10.1515/bmt-2018-0077
dc.identifier.endpage71
dc.identifier.issn0013-5585
dc.identifier.issn1862-278X
dc.identifier.issue1
dc.identifier.pmid31377730
dc.identifier.scopus2-s2.0-85070590124
dc.identifier.scopusqualityQ3
dc.identifier.startpage61
dc.identifier.urihttps://doi.org/10.1515/bmt-2018-0077
dc.identifier.urihttps://hdl.handle.net/20.500.13099/1703
dc.identifier.volume65
dc.identifier.wosWOS:000508008600006
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherWalter De Gruyter Gmbh
dc.relation.ispartofBiomedical Engineering-Biomedizinische Technik
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectcarpal tunnel syndrome
dc.subjectelectrophysiology
dc.subjectFourier analysis
dc.subjectneural network model
dc.titleA novel approach to the diagnostic assessment of carpal tunnel syndrome based on the frequency domain of the compound muscle action potential
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
PubMed İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu