A survey of Applied Psychological Services' models of the human operator

A historical perspective is presented in terms of the major features and status of two families of computer simulation models in which the human operator plays the primary role. Both task oriented and message oriented models are included. Two other recent efforts are summarized which deal with visual information processing. They involve not whole model development but a family of subroutines customized to add the human aspects to existing models. A global diagram of the generalized model development/validation process is presented and related to 15 criteria for model evaluation

A Classification Model for Sensing Human Trust in Machines Using EEG and GSR

Today, intelligent machines \emph{interact and collaborate} with humans in a way that demands a greater level of trust between human and machine. A first step towards building intelligent machines that are capable of building and maintaining trust with humans is the design of a sensor that will enable machines to estimate human trust level in real-time. In this paper, two approaches for developing classifier-based empirical trust sensor models are presented that specifically use electroencephalography (EEG) and galvanic skin response (GSR) measurements. Human subject data collected from 45 participants is used for feature extraction, feature selection, classifier training, and model validation. The first approach considers a general set of psychophysiological features across all participants as the input variables and trains a classifier-based model for each participant, resulting in a trust sensor model based on the general feature set (i.e., a "general trust sensor model"). The second approach considers a customized feature set for each individual and trains a classifier-based model using that feature set, resulting in improved mean accuracy but at the expense of an increase in training time. This work represents the first use of real-time psychophysiological measurements for the development of a human trust sensor. Implications of the work, in the context of trust management algorithm design for intelligent machines, are also discussed.Comment: 20 page

Customized design of hearing aids using statistical shape learning

3D shape modeling is a crucial component of rapid prototyping systems that customize shapes of implants and prosthetic devices to a patient’s anatomy. In this paper, we present a solution to the problem of customized 3D shape modeling using a statistical shape analysis framework. We design a novel method to learn the relationship between two classes of shapes, which are related by certain operations or transformation. The two associated shape classes are represented in a lower dimensional manifold, and the reduced set of parameters obtained in this subspace is utilized in an estimation, which is exemplified by a multivariate regression in this paper.We demonstrate our method with a felicitous application to estimation of customized hearing aid devices

Modelling mobile health systems: an application of augmented MDA for the extended healthcare enterprise

Mobile health systems can extend the enterprise computing system of the healthcare provider by bringing services to the patient any time and anywhere. We propose a model-driven design and development methodology for the development of the m-health components in such extended enterprise computing systems. The methodology applies a model-driven design and development approach augmented with formal validation and verification to address quality and correctness and to support model transformation. Recent work on modelling applications from the healthcare domain is reported. One objective of this work is to explore and elaborate the proposed methodology. At the University of Twente we are developing m-health systems based on Body Area Networks (BANs). One specialization of the generic BAN is the health BAN, which incorporates a set of devices and associated software components to provide some set of health-related services. A patient will have a personalized instance of the health BAN customized to their current set of needs. A health professional interacts with their\ud patients¿ BANs via a BAN Professional System. The set of deployed BANs are supported by a server. We refer to this distributed system as the BAN System. The BAN system extends the enterprise computing system of the healthcare provider. Development of such systems requires a sound software engineering approach and this is what we explore with the new methodology. The methodology is illustrated with reference to recent modelling activities targeted at real implementations. In the context of the Awareness project BAN implementations will be trialled in a number of clinical settings including epilepsy management and management of chronic pain

Cloud-based manufacturing-as-a-service environment for customized products

This paper describes the paradigm of cloud-based services which are used to envisage a new generation of configurable manufacturing systems. Unlike previous approaches to mass customization (that simply reprogram individual machines to produce specific shapes) the system reported here is intended to enable the customized production of technologically complex products by dynamically configuring a manufacturing supply chain. In order to realize such a system, the resources (i.e. production capabilities) have to be designed to support collaboration throughout the whole production network, including their adaption to customer-specific production. The flexible service composition as well as the appropriate IT services required for its realization show many analogies with common cloud computing approaches. For this reason, this paper describes the motivation and challenges that are related to cloud-based manufacturing and illustrates emerging technologies supporting this vision byestablishing an appropriate Manufacturing-as-a-Service environment based on manufacturing service descriptions