Model-Based Design of Experiments (MBDoE) techniques represent a valuable tool to increase the information content of clinical tests with the purpose to identify the set of parameters of physiological models of type 1...
详细信息
Abstract Model-Based Design of Experiments (MBDoE) techniques represent a valuable tool to increase the information content of clinical tests with the purpose to identify the set of parameters of physiological models ...
详细信息
Abstract Model-Based Design of Experiments (MBDoE) techniques represent a valuable tool to increase the information content of clinical tests with the purpose to identify the set of parameters of physiological models of type 1 diabetes mellitus. However, conventional MBDoE techniques are affected by some limitations. Prior uncertainty in the model parameters and model mismatch may lead the constrained design procedure to predict clinical tests that turn out to be suboptimal or, even worse, unsafe for the subject. Advanced MBDoE techniques, including online model-based redesign of experiments can be used to preserve the effectiveness of the experiment design sessions, exploiting in a more efficient way the nearly-continuous information flux coming from continuous glucose monitoring systems (CGMSs). In this paper a simulated case study is used to assess the impact of advanced redesign techniques on exploiting CGMSs data in the experiment design and successive parameter estimation for the identification of a complex physiological model of glucose homeostasis.
Model-based design of experiments (MBDoE) techniques are a useful tool to maximise the information content of experimental trials when the purpose is identifying the set of parameters of a deterministic model in a sta...
详细信息
Model-Based Design of Experiments (MBDoE) techniques can be a valuable tool to improve the information content of clinical tests when the purpose is to identify the set of parameters of physiological models in type 1 ...
详细信息
ISBN:
(纸本)9781846000386
Model-Based Design of Experiments (MBDoE) techniques can be a valuable tool to improve the information content of clinical tests when the purpose is to identify the set of parameters of physiological models in type 1 diabetes mellitus care. Recent advances on sensor technology allowed for the development of continuous glucose monitoring systems (CGMSs), where measurements can be collected with a frequency which is much higher than possible so far. In this paper a dynamic approach to model-based design of experiments is adopted to specifically tailor the design procedure to the features of a CGMS. A simulated case study is used to assess the impact of CGMSs in the experiment design and successive parameter estimation for the identification of a complex physiological model of glucose homeostasis. Results are compared to an MBDoE applied to a conventional discrete measurement system.
In fiber technology, the characterization of both morphology and physical features of fiber fabrics is of paramount importance. Usually, the key characteristics of fibrous materials are determined by time-consuming an...
详细信息
In fiber technology, the characterization of both morphology and physical features of fiber fabrics is of paramount importance. Usually, the key characteristics of fibrous materials are determined by time-consuming and possibly destructive laboratory analysis. In this paper, a multivariate and multiresolution software sensor is presented that exploits the information embedded in images of fibrous materials to measure the morphology of the product and also to estimate its morphological and physical characteristics. The soft sensor includes two artificial vision systems performing: 1) the direct measurement of the fiber diameter distribution and 2) the estimation of fiber diameter distribution and permeability from texture analysis. The soft sensor is tested in the case of scanning electron microscope images of polymer nanofiber membranes, and demonstrates to be accurate and reliable.
Model-based design of experiments (MBDoE) techniques are a useful tool to maximise the information content of experimental trials when the purpose is identifying the set of parameters of a deterministic model in a sta...
详细信息
Model-based design of experiments (MBDoE) techniques are a useful tool to maximise the information content of experimental trials when the purpose is identifying the set of parameters of a deterministic model in a statistically sound way. When samples are collected in a discrete way, the formulation of the optimal design problem is based on the maximisation of the expected information, usually calculated from discrete forms of the Fisher information matrix. However, if a continuous measurement system is available, information can be acquired gradually in a continuous way, and a new MBDoE approach is required to take into account the specificity of the measurement system. In this paper a novel design criterion is formulated by optimising a continuous measurement of the Fisher information matrix, with the purpose of reaching a statistically satisfactory estimation of model parameters in the easiest and quickest way. The benefits of the proposed strategy are discussed through a simulated case study, where the effectiveness of the design is assessed by comparison to a standard MBDoE approach.
暂无评论