Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals Subject The topic of the resource Brain signal; Brain-computer interface; Convolutional neural networks; Hand motion recognition; Machine learning Description An account of the resource Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals is a significant step. We saw a considerable increase in all the machine learning models when the moving average filter was applied to the raw EEG data. Feature extraction techniques like a fast fourier transform (FFT) and continuous wave transform (CWT) were used in this study; three types of features were extracted, i.e., FFT Features, CWT Coefficients and CWT scalogram images. We trained and compared different machine learning (ML) models like logistic regression, random forest, k-nearest neighbors (KNN), light gradient boosting machine (GBM) and XG boost on FFT and CWT features and deep learning (DL) models like VGG-16, Dense-Net201 and ResNet50 trained on CWT scalogram images. XG Boost with FFT features gave the maximum accuracy of 88%. 2022 CRL Publishing. All rights reserved. Creator An entity primarily responsible for making the resource Altameem A.; Sachdev J.S.; Singh V.; Poonia R.C.; Kumar S.; Saudagar A.K.J. Source A related resource from which the described resource is derived Computer Systems Science and Engineering, Vol-42, No. 3, pp. 1095-1107. Publisher An entity responsible for making the resource available Tech Science Press Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.32604/csse.2022.023256" target="_blank" rel="noreferrer noopener">https://doi.org/10.32604/csse.2022.023256</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124945126&amp;doi=10.32604%2Fcsse.2022.023256&amp;partnerID=40&amp;md5=3e9a4ac7e2155cc4705f1e8f9b8b6b63" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124945126&amp;doi=10.32604%2fcsse.2022.023256&amp;partnerID=40&amp;md5=3e9a4ac7e2155cc4705f1e8f9b8b6b63</a> Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 2676192; CODEN: CSSEE Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Altameem A., Department of Computer Science, College of Applied Studies, King Saud University, Riyadh, 11495, Saudi Arabia; Sachdev J.S., Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, 303007, India; Singh V., Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, 303007, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia