Results 241 to 250 of about 1,020,025 (280)

Validity of a Wearable Digital Insole for Assessing Gait ON and OFF in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Gait impairment is a distinctive symptom of Parkinson's disease that negatively impact mobility. We assessed the validity of wearable digital insoles against a validated reference gait analysis system for measuring select gait characteristics in patients with Parkinson's disease. Methods A comparative analysis between digital insoles
Deborah A. Hall, Kimberly Kwei, Rolando J. Acosta, Bharatkumar Koyani, Erin Robertson, Pratyush Rai, Roland Barge, Emily Timm, Nicollette L. Purcell, Natasha Desai, Dhanesh Patel, Ana‐Maria Visoiu‐Knapp, Samuel Stuart, Rinol Alaj, Matthew F. Wipperman, Oren Levy, Joan A. O'Keefe   +16 more
wiley   +1 more source

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown, Giulia Carli, Prabesh Kanel, Stiven Roytman, Jaimie Barr, Nicolaas I. Bohnen, Roger L. Albin   +6 more
wiley   +1 more source

Functional data analysis of lower-limb joint kinematics during badminton lunges under fatigue. [PDF]

Front Bioeng Biotechnol
Fang Y, Zhang X, Sun Y, Wu H, Pei H, Gao J, Liu J, Zhu Q, Gao Y.   +8 more
europepmc   +1 more source

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Principal Components Analysis of Sampled Functions

Psychometrika, 1986
This paper describes a technique for principal components analysis of data consisting of n functions each observed at p argument values. This problem arises particularly in the analysis of longitudinal data in which some behavior of a number of subjects is measured at a number of points in time.
Besse, Philippe, Ramsay, J. O.
openaire   +1 more source

Supervised functional principal component analysis

Statistics and Computing, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yunlong Nie, Liangliang Wang, Baisen Liu, Jiguo Cao   +3 more
openaire   +1 more source

Sensitivity analysis in functional principal component analysis

Computational Statistics, 2005
Penalized functional principal components analysis (PCA) is considered. Sensitivity analysis based on the empirical influence functions (EIF) is discussed. EIFs are calculated for a fixed penalty parameter \(\lambda\) and for \(\lambda\) obtained by cross-validation. Cook's distances are proposed for single-case diagnostics.
Yamanishi, Yoshihiro, Tanaka, Yutaka
openaire   +2 more sources

Uncertainty in functional principal component analysis

Journal of Applied Statistics, 2016
ABSTRACTPrincipal component analysis (PCA) and functional principal analysis are key tools in multivariate analysis, in particular modelling yield curves, but little attention is given to questions of uncertainty, neither in the components themselves nor in any derived quantities such as scores.
James Sharpe, Nick Fieller
openaire   +1 more source

Robust Functional Principal Component Analysis

2014
When dealing with multivariate data robust principal component analysis (PCA), like classical PCA, searches for directions with maximal dispersion of the data projected on it. Instead of using the variance as a measure of dispersion, a robust scale estimator s n may be used in the maximization problem.
Juan Lucas Bali, Graciela Boente
openaire   +1 more source