Learn More
A Gaussian process functional regression model is proposed for the analysis of batch data. Covariance structure and mean structure are considered simultaneously, with the covariance structure modeled by a Gaussian process regression model and the mean structure modeled by a functional regression model. The model allows the inclusion of covariates in both(More)
A Gaussian process functional regression model is proposed for the analysis of batch data. Covariance structure and mean structure are considered simultaneously , with the covariance structure modelled by a Gaussian process regression model and the mean structure modelled by a functional regression model. The model allows the inclusion of covariates in both(More)
Shi et al. (2006) proposed a Gaussian process functional regression (GPFR) model to model functional response curves with a set of functional covariates. Two main problems are addressed by this method: modelling nonlinear and nonparametric regression relationship and modelling covariance structure and mean structure simultaneously. The method gives very(More)
We propose a new semiparametric model for functional regression analysis, combining a parametric mixed-effects model with a nonparametric Gaussian process regression model, namely a mixed-effects Gaussian process functional regression model. The parametric component can provide explanatory information between the response and the covariates, whereas the(More)
We present an evaluation of the cross-sectional and longitudinal validity (sensitivity to change) of a new algorithm to assess upper limb function generated automatically during play of a bespoke, professionally-written action video game (Circus Challenge Assessment Game, CCAG). The subjects were 33 patients with hemiplegia after stroke (aged 33-81 years),(More)
In this paper we describe how a video game designed to deliver a rehabilitation therapy can produce data of a standard that is clinically useful. Our approach is based entirely on commodity video game hardware, making our solution one that may be delivered in a cost efficient manner. The step of ensuring data fidelity was crucial in allowing clinical(More)