Rita Dario

Computational-based volatile organic compounds discrimination: An experimental low-cost setup

In this work, an array of low-cost cross-sensitive sensors is used for discriminating the best candidate within a set of volatile organic compounds (VOCs). The challenge of our experimental setting is to deal with the problems of low selectivity, especially in normal operating conditions, so that ambiguous sensor responses (i.e. referable to more than one VOC) can be given, at least, a qualitative interpretation. In order to carry out the signal disambiguation task, a computational technique employing simple classifying rules and fuzzy descriptions has been engineered. The basic idea is that, if the same gas is actually measured by two or more sensors, then the estimated concentrations will show a low variance, with an accuracy related to the number of concordant sensors. Experiments show that, despite the cheapness of the setup and the coarse-grained nature of the provided response, encouraging results can be obtained and prospective work can follow.

Air quality control for health care centres. The application of an intelligent distributed system

Aim of this paper is to present an intelligent distributed monitoring system designed to monitor the air quality in specific indoor environments. The proposed architecture is very flexible and the used design principles can be applied to various indoor and outdoor environments. In this work the authors describe the features of this system tuned for monitoring the air quality in a healthcare center.

Medical environment spot exposure: A solid state personal dosimeter

The pollutant presence in hospital is regulated for biological and environmental risk monitoring. Typically, biological and chemical samplers are used to obtain information about air quality and air biological contamination according to European policy and regulations. Currently, air quality data are available to the hospital direction after a few weeks from environmental sampling.

Evaluation of smartphone usage in neurological pathologies diagnosis

Population ageing, i.e. the increase of the median age in the population, has become a pressing matter, due to a significant rise in health-care expenses, which, if not controlled, may destabilize welfare mechanisms. To face this problem, various approaches have already been presented in literature: some of these methods acquire pathology-relevant data using ad-hoc systems (i.e. sensor arrays), while others employs commercial devices, like wearable or smartphones; however, there are several issues that such systems must address, i.e. the meaningfulness of sensed data, or the wellness of the patients in the follow-up phase. The aim of this work is to propose a medical decision support system, specifically oriented to the acquisition of data related to neurological pathologies, whose final aim is to build an extended medical knowledge base, which will be used by skilled professionals in the diagnosis phase of the pathology; to improve the comfort of the patients, a smartphone medical app has been developed and tested, therefore evaluating the relevance of the data acquired by sensors embedded in an Android smartphone, and assessing the overall feasibility of such a decision support system.

IoT and CPS applications based on wearable devices. A case study: Monitoring of elderly and infirm patients

After briefly discussing the loT and Cyber physical device main features, the application of wearable devices was examined. The constrains of this class of application are in the greatest interest of the researchers and enterprises for the interested in many possible uses of it. The Apulia Region has issued a call for proposals for “Innonetwork sostegno alle attività di R&S per lo sviluppo di nuove tecnologie sostenibili, di nuovi prodotti e servizi” by requesting innovative projects in the field of medical monitoring. The paper focuses on the defining of some guidelines for a possible application of a wearable devices, with sensor and internet connections suitable for monitoring of elderly and infirm peoples also in the remote follow-up phase. The issue of monitoring long-term care patients introduces an array of technical challenges in designing systems and algorithms.

Augmented reality for artificial optical radiation measurement

Augmented reality application, has received considerable interest in recent years with the advent of specialized applications and data fusion from different visual sources. In this paper, we present a novel mobile augmented reality system for artificial optical radiation (AOR) identification and measurement. The system has been designed to help experts (both medical doctors and engineers) deal with AOR related problem in their fields according to the European Directive 2006/25/EC (Occupational health and safety). An innovative tracking system, based on image retrieval paradigms, has been used in image registration.

Modelling the Clinical Risk: RFID vs Barcode

This chapter proposes an approach that can improve the identification of patients, products, equipment and so on in a hospital. The aim is to better the management of the clinical risk by automating the process through the use of Radio Frequency IDentification (RFID). The clinical risk management refers to the procedures for avoiding risks associated with direct patient care. It is the analysis about the probability of a patient being victim of an adverse event or inconvenience resulted, although involuntary, from improper medical care provided during the hospitalization. Research defines that the common denominator of almost all adverse clinical events is the lack of the patient traceability. In the specific context of a hospital, “traceability of patients” means managing a whole set of input and output data related to those processes defined as critical for clinical facilities. In this work we will discuss a model to archive and manipulate data concerning the proposed system. RFID is, in fact, identified as a method for storing and retrieving data remotely by using small and cheap devices called RFID tags or transponders. For applying this technology in hospital environment it is necessary to build a network of these objects, each one with a unique number. So, only if there is a valid model to manage the produced output, one can easily retrieve information and realize an interesting use case. In the proposed model, the adoption of an active instrument for automatic patient identification and assistance can be considered as the central entity of the process: “medical treatment of a patient”, this includes potentially every activity from initial consultation through discharge of a surgical patient. In particular, this approach allows for simplifying the reality in terms of observable entities and supporting a higher degree of interconnection among those sections that traditionally are called “functional areas” of the hospital organization. Indeed, a lot of different actors characterize a clinical environment and the use of RFID seems to be capable to track all of them and optimize their interaction (Liao et al., 2006). The proposed RFID applications are targeted to the:  Verification of positive patient identification. This is realized by means of a smart wristband for each patient. The tag contains information about the patient name, date of