Biomedical subjects

Sunil L Kukreja

Publications and source records attributed to Sunil L Kukreja.

3 recordsLinked to original sources

PubMed2005

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR.

A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically requires a preprocessing step to classify the observed data according to a mode of operation. A further consequence of the switched nature of these systems is that data available for parameter estimation of any subsystem may be inadequate. As such, identification and parameter estimation of multimode systems remains an unresolved problem. In this paper, we 1) show that the NARMAX model structure can be used to describe the impulsive-smooth behavior of switched systems, 2) propose a modified extended least squares (MELS) algorithm to estimate the coefficients of such models, and 3) demonstrate its applicability to simulated and real data from the Vestibulo-Ocular Reflex (VOR). The approach will also allow the identification of other nonlinear bio-systems, suspected of containing "hard" nonlinearities.

Algorithms↗

PubMed2004

Bootstrapped DEPICT for error estimation in PET functional imaging.

Basis pursuit denoising is a new approach for data-driven estimation of parametric images from dynamic positron emission tomography (PET) data. At present, this kinetic modeling technique does not allow for the estimation of the errors on the parameters. These estimates are useful when performing subsequent statistical analysis, such as, inference across a group of subjects or when applying partial volume correction algorithms. The difficulty with calculating the error estimates is a consequence of using an overcomplete dictionary of kinetic basis functions. In this paper, a bootstrap approach for the estimation of parameter errors from dynamic PET data is presented. This paper shows that the bootstrap can be used successfully to compute parameter errors on a region of interest or parametric image basis. Validation studies evaluate the methods performance on simulated and measured PET data ([(11)C]Diprenorphine-opiate receptor and [(11)C]Raclopride-dopamine D(2) receptor). The method is presented in the context of PET neuroreceptor binding studies, however, it has general applicability to a wide range of PET/SPET radiotracers in neurology, oncology and cardiology.

Adult↗

PubMed2003

NARMAX representation and identification of ankle dynamics.

Representation and identification of a parallel pathway description of ankle dynamics as a model of the nonlinear autoregressive, moving average exogenous (NARMAX) class is considered. A nonlinear difference equation describing this ankle model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to ankle dynamics and its properties investigated via continuous-time simulations of experimental conditions. Simulation results show that 1) the outputs of the NARMAX model match closely those generated using continuous-time methods and 2) NARMAX identification methods applied to ankle dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental human ankle data models with high cross-validation variance accounted for.

Ankle↗