G. De Pietro

A user interface for VR-ready 3D medical imaging by off-the-shelf input devices

The distinctiveness of clinical environments demands specific solutions in the design of both usable and practical user interfaces for 3D medical imaging. In this work, a novel user interface to provide a direct interaction in 3D space by off-the-shelf input devices is proposed. The interface, which has been implemented and integrated into an open-source medical image viewer, features a depth-enhanced mouse pointer and a novel rotation technique that uses the objects geometry as the rotation handle. The usability of the proposed approach is evaluated to show its effectiveness for use in professional 3D imaging applications.

Tools for the Rapid Prototyping of Provably Correct Ambient Intelligence Applications

Ambient Intelligence technologies have not yet been widely adopted in safety critical scenarios. This principally has been due to fact that acceptable degrees of dependability have not been reached for the applications that rely on such technologies. However, the new critical application domains, like Ambient Assisted Living and Smart Hospitals, which are currently emerging, are increasing the need for methodologies and tools that can improve the reliability of the final systems. This paper presents a middleware architecture for safety critical Ambient Intelligence applications which provides the developer with services for runtime verification. It is now possible to continuously monitor and check the running system against correctness properties defined at design time. Moreover, a visual tool which allows the formal design of several of the characteristics of an Ambient Intelligence application and the automatic generation of setting up parameters and code for the middleware infrastructure is also presented.

Transformation of probability distribution into fuzzy set interpretable with likelihood view

Recent research agrees on the utility of fuzzy reasoning for the development of Decision Support Systems, which help to classify clinical data. In this context, methods or techniques for representing fuzzy terms in the form of interpretable fuzzy sets obtained from numerical data are strongly required. Typically, in medical settings, statistical data are available or can be obtained from rough data, in the form of probability distributions or likelihood functions. Until now, no theoretical approach was proposed for transforming a probability distribution into a likelihood view fuzzy set. In this paper, a method is developed which generalizes some existing approaches by giving them a theoretical justification. The method enables the construction of normal fuzzy sets, which can be chosen to have a triangular or trapezoidal shape where lateral edges are adapted depending on the input probability distribution. The method was assessed through its application to a simulated normal probability distribution and to real case study pertaining the classification of Multiple Sclerosis lesions.

A framework for ECG denoising for mobile devices

Wearable sensors are widely adopted for the provision of healthcare services. Unfortunately the noise always degrades the quality of the acquired signals. In this paper, we propose a framework for mobile ECG denoising, based on a novel numerical scheme with low computational requirements. The proposed system is able to store a signal from a wearable sensor and process it in a remote way or directly on the device.

User-Friendly Inspection of Medical Image Data Volumes in Virtual Environments

In many fields of medicine interactive virtual environments can offer enhanced visualization and manipulation of three-dimensional objects, reconstructed from high-quality scans of human organs. Stereoscopic systems provide users with a natural depth perception about the spatial nature of the structures of interest; moreover advanced user-friendly interfaces, by allowing a natural and intuitive interaction, can strengthen the feeling of being immersed, so to offer clinicians the possibility to act how they do in the real life. In order to enhance the sense of realism specially in medical computer-assisted education, training and diagnostic fields, it is necessary to have a system in which every action can be executed directly into the 3D world without switching to a 2D visualization mode. In this paper we present new interaction techniques to select and extract a volume-of-interest (VOI) in a semi-immersive interactive environment, by using a user-friendly wireless interface, suitable to implement pointing and manipulation features with 6 DOF.

A New Approach For Handling 3D Medical Data In An Immersive Environment

Medical Imaging applications use images coming from different sources such as magnetic resonance imaging (MRI), computer tomography (CT), positron emission tomography (PET), to generate 3D data. Starting from these volumetric data, applications reconstruct 3D models of anatomical structures which could be manipulated and analyzed. In this paper we present a new approach for the visualization and interaction with volumetric datasets in a fully immersive environment. It allows to handle the reconstructed models directly within the virtual scene; in particular a technique is described for outlining the Volume Of Interest (VOI) functionality in a three-dimensional dataset for a visual interactive inspection and manipulation of the organ of interest.

A lazy evaluation approach for mobile reasoning in DSSs

Recently, a new mobile generation of decision support systems (DSSs) is appearing to face a set of new challenging scenarios, where information must be used anywhere for supporting the decision-making tasks seamlessly and ubiquitously. In this respect, this paper presents a lazy evaluation approach for reasoning in mobile knowledge-based DSSs in order to grant an efficient handling of memory and computational resources. The approach relies on knowledge representation and reasoning facilities to face and efficiently reason on the continuous and real-time flow of data. The core of the approach is a lazy pattern matching algorithm, specifically designed and implemented as a light-weight solution suitable for resource-limited mobile devices with the final aim of improving performance in real-time and intensive applications.

Middleware Services for Multimodal Interactions in Smart Environments

Smart and intelligent environments can proficiently benefit from a new generation of multimodal dialog systems, which enable users to interact in natural ways like voice, gesture, facial motions, and so on. However, in order to make this possible, it is necessary to integrate such systems and services, possibly in a transparent way. In the present paper, we propose (i) an architectural model for multimodal smart environments; (ii) an agent-based middleware infrastructure that provides basic components for the integration of multimodal interaction systems; and, (iii) a tool for rapid-prototyping, which automatically customizes some middleware components to implement multimodal interaction mechanisms for the environments application services.

A multi-level fuzzy inference system for developing DSS based on clinical guidelines

Clinical Decision Support Systems (CDSSs) are typically based on clinical guidelines explicitly formalized in the form of rules for reproducing the physicians decisionmaking process and, also, improving the efficiency of medical practices. With the aim of building CDSSs able to represent uncertainty existing in clinical guidelines and efficiently reason on a huge number of inter-connected rules, this paper presents a multi-level fuzzy inference system offering the following set of specifically-devised functionalities: (i) fuzzy rules can be organized in one or more groups of positive evidence rules, where each group is able to interact with other ones by properly chaining their conclusions; (ii) rules inside a group are independently processed and evaluated; (iii) each group of rules can be customized by means of a peculiar configuration for the inference; (iv) a fuzzy ELSE rule can be associated to a group for assembling all the negative evidence for a specific situation. A proof of concept scenario is finally given to describe how the proposed solution can be applied.

Properties Evaluation of an Approach Based on Probability-Possibility Transformation

The recent research on classification problems, in fields where vague concepts have to be considered, agree on the utility of fuzzy logic. An important step of inference engines preparation is the definition of fuzzy sets. When probability distributions of concerned variables are known, they can be used to define fuzzy sets, and different methods allow to perform this transformation. A method recently proposed by authors is compared here with other existing methods, in terms of assumptions and properties about the obtained fuzzy set, also considered with respect to the probability distribution it was calculated from. The best existing transformation in terms of compromise between consistency and specificity results to be a particular case of the proposed transformation, which can therefore be considered a more general method. Moreover, it enables, with a small loss of consistency, to find more interpretable fuzzy sets, while the case of less specific fuzzy sets is comprised and justified.