Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction

Recent breakthroughs with numerous visual experiences using mobile devices encourage the research of human-computer interaction (HCI) involving hand gesture recognition for Holograms, Virtual Reality, and Augmented Reality. The rise of these technologies allows educators in medical segments to apply...

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Autores principales:	Zainal Abdul Kahar, Puteri Suhaiza Sulaiman, Fatimah Khalid, Azreen Azman
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Hand gesture recognition dimensionality reduction machine learning hologram Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/4e266d5f8ae74008b6476774fe2c96ec
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spelling	oai:doaj.org-article:4e266d5f8ae74008b6476774fe2c96ec2021-11-09T00:01:23ZSkeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction2169-353610.1109/ACCESS.2021.3123570https://doaj.org/article/4e266d5f8ae74008b6476774fe2c96ec2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9591567/https://doaj.org/toc/2169-3536Recent breakthroughs with numerous visual experiences using mobile devices encourage the research of human-computer interaction (HCI) involving hand gesture recognition for Holograms, Virtual Reality, and Augmented Reality. The rise of these technologies allows educators in medical segments to apply new pedagogy by interacting with virtual content in a coherent learning environment. This paper proposed the Central Nervous System (CNS) interaction using the Skeleton Joints Moment (SJM) approach for dimension reduction with k Nearest Neighbour (k-NN) for hand gesture classification. Over the past few decades, researchers have proposed various techniques in dimension reduction. One of the methods is principal component analysis (PCA). Experimental results indicated that the SJM technique has similar accuracy to PCA, where both methods showed 96% of prediction using hand skeleton joints data. In addition, PCA has a higher uncertainty of mean error 0.75 compared to SJM at only 0.01. Furthermore, PCA has the worst complexity of <inline-formula> <tex-math notation="LaTeX">$O(min(p^{3},n^{3}))$ </tex-math></inline-formula> where SJM <inline-formula> <tex-math notation="LaTeX">$O(n/d)$ </tex-math></inline-formula>. Evaluation results using the T-Test showed a significant difference between SJM and PCA where <inline-formula> <tex-math notation="LaTeX">$p < 0.05$ </tex-math></inline-formula>. Thus, there is evidence to reject the null hypothesis.Zainal Abdul KaharPuteri Suhaiza SulaimanFatimah KhalidAzreen AzmanIEEEarticleHand gesture recognitiondimensionality reductionmachine learninghologramElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 146640-146652 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Hand gesture recognition dimensionality reduction machine learning hologram Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Hand gesture recognition dimensionality reduction machine learning hologram Electrical engineering. Electronics. Nuclear engineering TK1-9971 Zainal Abdul Kahar Puteri Suhaiza Sulaiman Fatimah Khalid Azreen Azman Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction
description	Recent breakthroughs with numerous visual experiences using mobile devices encourage the research of human-computer interaction (HCI) involving hand gesture recognition for Holograms, Virtual Reality, and Augmented Reality. The rise of these technologies allows educators in medical segments to apply new pedagogy by interacting with virtual content in a coherent learning environment. This paper proposed the Central Nervous System (CNS) interaction using the Skeleton Joints Moment (SJM) approach for dimension reduction with k Nearest Neighbour (k-NN) for hand gesture classification. Over the past few decades, researchers have proposed various techniques in dimension reduction. One of the methods is principal component analysis (PCA). Experimental results indicated that the SJM technique has similar accuracy to PCA, where both methods showed 96% of prediction using hand skeleton joints data. In addition, PCA has a higher uncertainty of mean error 0.75 compared to SJM at only 0.01. Furthermore, PCA has the worst complexity of <inline-formula> <tex-math notation="LaTeX">$O(min(p^{3},n^{3}))$ </tex-math></inline-formula> where SJM <inline-formula> <tex-math notation="LaTeX">$O(n/d)$ </tex-math></inline-formula>. Evaluation results using the T-Test showed a significant difference between SJM and PCA where <inline-formula> <tex-math notation="LaTeX">$p < 0.05$ </tex-math></inline-formula>. Thus, there is evidence to reject the null hypothesis.
format	article
author	Zainal Abdul Kahar Puteri Suhaiza Sulaiman Fatimah Khalid Azreen Azman
author_facet	Zainal Abdul Kahar Puteri Suhaiza Sulaiman Fatimah Khalid Azreen Azman
author_sort	Zainal Abdul Kahar
title	Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction
title_short	Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction
title_full	Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction
title_fullStr	Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction
title_full_unstemmed	Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction
title_sort	skeleton joints moment (sjm): a hand gesture dimensionality reduction for central nervous system interaction
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/4e266d5f8ae74008b6476774fe2c96ec
work_keys_str_mv	AT zainalabdulkahar skeletonjointsmomentsjmahandgesturedimensionalityreductionforcentralnervoussysteminteraction AT puterisuhaizasulaiman skeletonjointsmomentsjmahandgesturedimensionalityreductionforcentralnervoussysteminteraction AT fatimahkhalid skeletonjointsmomentsjmahandgesturedimensionalityreductionforcentralnervoussysteminteraction AT azreenazman skeletonjointsmomentsjmahandgesturedimensionalityreductionforcentralnervoussysteminteraction
_version_	1718441383409221632

Skeleton Joints Moment (SJM): A Hand Gesture Dimensionality Reduction for Central Nervous System Interaction

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