Motion Classification Using Proposed Principle Component Analysis Hybrid K-Means Clustering

ISSN Print: 1947-3931
ISSN Online: 1947-394X
www.scirp.net/journal/eng
E-mail: [email protected]

Citations

"Motion Classification Using Proposed Principle Component Analysis Hybrid K-Means Clustering"
written by Ching Yee Yong, Rubita Sudirman, Nasrul Humaimi Mahmood, Kim Mey Chew,
published by Engineering, Vol.5 No.5B, 2013

has been cited by the following article(s):

[1]	Twenty-four hour activity-count behavior patterns associated with depressive symptoms: A big data-machine learning approach
	medRxiv, 2023

[2]	The Correlation of Gyroscope Axial Velocities
	Journal of Mechanical Materials and …, 2023

[3]	Feature selection for unsupervised machine learning of accelerometer data physical activity clusters–A systematic review
	Gait & Posture, 2021

[4]	An Automatic Detection of Rugby Union Player Motions Using Time Series Analysis
	2017

[5]	Model Selection Based on Bayes Factor/Seleção de modelo com base no Bayes Factor
	2017

[1]	Interstride Variation in EEG Power Spectra of Younger and Older Adults Walking at a Range of Gait Speeds IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2026 DOI:10.1109/TNSRE.2026.3656061

[2]	Gait speed-related changes in electrocortical activity in younger and older adults Journal of Neurophysiology, 2025 DOI:10.1152/jn.00544.2024

[3]	Feature selection for unsupervised machine learning of accelerometer data physical activity clusters – A systematic review Gait & Posture, 2021 DOI:10.1016/j.gaitpost.2021.08.007

[4]	Interrelation of Precessed Motions of the Gyroscope World Journal of Mechanics, 2021 DOI:10.4236/wjm.2021.119013

Top