Results 1 to 10 of about 16,610 (139)

Using functional principal component analysis (FPCA) to quantify sitting patterns derived from wearable sensors [PDF]

International Journal of Behavioral Nutrition and Physical Activity
Background Sedentary behavior (SB) is a recognized risk factor for many chronic diseases. ActiGraph and activPAL are two commonly used wearable accelerometers in SB research. The former measures body movement and the latter measures body posture.
Rong W. Zablocki, Sheri J. Hartman, Chongzhi Di, Jingjing Zou, Jordan A. Carlson, Paul R. Hibbing, Dori E. Rosenberg, Mikael Anne Greenwood-Hickman, Lindsay Dillon, Andrea Z. LaCroix, Loki Natarajan   +10 more
doaj   +7 more sources

Dimensionality reduction of COSMO-RS molecular descriptor using functional principal component analysis (FPCA) for organic solvent mapping [PDF]

RSC Advances
Methodology for the generation of the σ-potential FPCA mapping.
Luis Eduardo Ramirez Cardenas, Rachid Ouaret, Vincent Gerbaud, Ivonne Rodriguez Donis, Sophie Thiebaud-Roux   +4 more
europepmc   +4 more sources

Lower-limb surface electromyographic differences in roundhouse kicks between elite and sub-elite taekwondo athletes: a functional principal component analysis [PDF]

Frontiers in Physiology
PurposeThis study aimed to investigate the functional characteristics and distinctions in lower-limb electromyography (EMG) time-series data during roundhouse kicks performed by elite (n = 10) and sub-elite (n = 10) Taekwondo athletes, using Functional ...
Jianbo Sun, Yifei Wang, Jingyuan Sun, Delong Dong, Shazlin Shaharudin   +4 more
doaj   +3 more sources

Lower-limb muscle activation patterns during the taekwondo roundhouse kick in elite and youth athletes: a functional principal component analysis [PDF]

Frontiers in Bioengineering and Biotechnology
ObjectiveThe taekwondo roundhouse kick is a fundamental and performance-critical technique that requires precise lower-limb muscle coordination. However, previous studies have mainly focused on discrete electromyographic variables, providing limited ...
Jianbo Sun, Jingyuan Sun, Gang Sun, Liang Yin, Shazlin Shaharudin, Shazlin Shaharudin   +5 more
doaj   +3 more sources

Predicting progressive vision loss in glaucoma patients using functional principal component analysis and electronic health records [PDF]

Frontiers in Ophthalmology
BackgroundGlaucoma is a leading cause of irreversible blindness worldwide. Predicting a patient’s future clinical trajectory would help physicians personalize management. We present a novel approach for predicting patient visual field (VF) progression by
Rithvik Krishna Donnipadu, Maxim Sivolella, Cody Carroll, Cody Carroll, Sophia Y. Wang   +4 more
doaj   +3 more sources

Prediction of Lithium-Ion Battery Capacity by Functional Principal Component Analysis of Monitoring Data

Applied Sciences, 2022
The lithium-ion (Li-ion) battery is a promising energy storage technology for electronics, automobiles, and smart grids. Extensive research was conducted in the past to improve the prediction of the remaining capacity of the Li-ion battery.
MD Shoriat Ullah, Kangwon Seo
doaj   +4 more sources

Functional principal component analysis (FPCA) on remote sensing data and longitudinal studies

, 2021
This dissertation consists of three main pieces of my Ph.D. dissertation, which shapes my research on multivariate functional data, change-point detection, asynchronous longitudinal data, and remote sensing data applications. The first project is motivated by NASA's first dedicated \ce{CO2} monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2)
Xinyue Chang
openaire   +5 more sources

SpaFun: discovering domain-specific spatial expression patterns and new disease-relevant genes using functional principal component analysis. [PDF]

Brief Bioinform
SpaFun is a novel, non-model-based method developed to address limitations in existing spatially variable gene (SVG) detection techniques, particularly for large-scale spatially resolved transcriptomics (SRT) datasets.
Jiang X, Guo Y, Guo L, Zhong L, Wang J, Xiao G, Li Q, Xu L.   +7 more
europepmc   +2 more sources

Application of Functional Principal Component Analysis in the Spatiotemporal Land-Use Regression Modeling of PM_2.5

Atmosphere, 2023
Functional data are generally curves indexed over a time domain, and land-use regression (LUR) is a promising spatial technique for generating high-resolution spatial estimation of retrospective long-term air pollutants.
Mahmood Taghavi, Ghader Ghanizadeh, Mohammad Ghasemi, Alessandro Fassò, Gerard Hoek, Kiavash Hushmandi, Mehdi Raei   +6 more
doaj   +2 more sources

Multilevel Multivariate Functional Principal Component Analysis of Evoked and Induced Event-Related Spectral Perturbations. [PDF]

Stat Biosci
Event-related spectral perturbations (ERSPs) capture dynamic changes in electroencephalography (EEG) power across frequency and trial time. Even though they are obtained at the trial level, they are commonly averaged across trials and analyzed at the ...
Dong M, Telesca D, Dickinson A, Sugar C, Webb SJ, Jeste S, Levin AR, Shic F, Naples A, Faja S, Dawson G, McPartland JC, Şentürk D.   +12 more
europepmc   +2 more sources