Publication:
The Usage of Constrained Independent Component Analysis to Reduce Electrode Displacement Effects in Real-Time Surface Electromyography-Based Hand Gesture Classifications

Simple item page
dc.contributor.authorBAŞPINAR, ULVİ
dc.contributor.authorsBAŞPINAR U., Taştan Y., VAROL H. S.
dc.date.accessioned2023-03-31T06:40:07Z
dc.date.available2023-03-31T06:40:07Z
dc.date.issued2022-12-01
dc.description.abstractAim: In real-time control of prosthesis, orthosis, and human–computer interface applications, the displacement of surface electrodes may cause a total disruption or a decline in the classification rates. In this study, a constrained independent component analysis (cICA) was used as an alternative method for addressing the displacement problem of surface electrodes. Materials and Methods: The study was tested by classifying six‑hand gestures offline and in real‑time to control a robotic arm. The robotic arm has five degrees of freedom, and it was controlled using surface electromyography (sEMG) signals. The classification of sEMG signals is realized using artificial neural networks. cICA algorithm was utilized to improve the performance of classifiers due to the negative effect of electrode displacement issues. Results: In the study, the classification results of the cICA applied and unapplied sEMG signals were compared. The results showed that the proposed method has provided an increase between 4% and 13% in classifications. The average classification rates for six different hand gestures were calculated as 96.66%. Conclusions: The study showed that the cICA method enhances classification rates while minimizing the impact of electrode displacement. The other advantage of the cICA algorithm is dimension reduction, which is important in real time applications. To observe the performance of the cICA in the real-time application, a robotic arm was controlled using sEMG signals. Keywords: Classifier, constrained independent component analysis, electrode, surface electromyography
dc.identifier.citationBAŞPINAR U., Taştan Y., VAROL H. S., "The Usage of Constrained Independent Component Analysis to Reduce Electrode Displacement Effects in Real-Time Surface Electromyography-Based Hand Gesture Classifications", The Journal of Neurobehavioral Sciences, cilt.9, sa.3, ss.107-113, 2022
dc.identifier.doi10.4103/jnbs.jnbs_34_22
dc.identifier.endpage113
dc.identifier.issn2149-1909
dc.identifier.issue3
dc.identifier.startpage107
dc.identifier.urihttps://uskudar.edu.tr/assets/uploads/dergi/4/file/jnbs-9-3-kapakli_6ocak.pdf
dc.identifier.urihttps://hdl.handle.net/11424/288029
dc.identifier.volume9
dc.language.isoeng
dc.relation.ispartofThe Journal of Neurobehavioral Sciences
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectClassifier
dc.subjectconstrained independent component analysis
dc.subjectelectrode
dc.subjectsurface electromyography
dc.titleThe Usage of Constrained Independent Component Analysis to Reduce Electrode Displacement Effects in Real-Time Surface Electromyography-Based Hand Gesture Classifications
dc.typearticle
dspace.entity.typePublication
local.avesis.idce010480-262b-4e3f-b8f8-9a1941cae9f5
relation.isAuthorOfPublication871cff99-4107-488b-bd17-6370f89e619b
relation.isAuthorOfPublication.latestForDiscovery871cff99-4107-488b-bd17-6370f89e619b

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
file.pdf
Size:
1.83 MB
Format:
Adobe Portable Document Format
Download

Collections

Research Outputs