THE TECHNICAL MANAGEMENT OF HEALTH INFORMATION SYSTEMS

The technical management of ICT/Telemedicine Services is one Hospital Manager's crucial problem. The Biomedical Technologies Market has clearly shown that technical support to the user is one of the most critical issues that contribute to guarantee the quality of service in High-Tech applications. Therefore the ICT/Telemedicine Services, which belong to the high innovation area as well, require adequate competencies and human resources in order to provide users with a proper technical support. All these technologies require on the one hand a specialist who normally works remotely (II level support) and on the other hand an ordinary management activity (I level technical support) in order to avoid that medical staff stop their work in the operative env

Study of magnetic switch for surface plasmon-polariton circuits

In recent years, technological development has focused on the construction of ever smaller devices, characterized by dimensions limited to the nanometer order and by a very low energy requirement to be able to function. This allows them to be integrated into chips, which are then able to perform many tasks from filtering to computation. Here, we present a magnetic switch capable of working with surface plasmon polaritons

Innovative and non-invasive method for the diagnosis of dyschromatopsia and the re-education of the eyes

Objective Dyschromatopsia is a pathology that afflicts many people even if, in most cases, they are not aware of it. The pathology, in fact, is not disabling in everyday life even if it is limiting from some points of view. Once diagnosed, dyschromatopsia is generally not investigated further: it is not known exactly how it manifests itself and with what extent. Furthermore, since it is a genetic pathology, it is “condemned” not to be resolvable. Biological neural networks have shown the capability to readapt their structure in order to overcome sensory malfunctions or neuronal damage. We propose a diagnostic algorithm capable of qualitatively and quantitatively assessing the degree of visual impairment due to the presence of congenital or acquired dyschromatopsia. The algorithm can also be easily integrated for its possible therapeutic use. Methods The application of a novel approach based on an innovative algorithm for the diagnosis of dyschromatopsia and plastic reeducation training of the eye is proposed. Results Our algorithm provides an accurate measure of the degree of dyschromatopsia severity in patients quickly and noninvasively. In addition, it can be used for a reeducational training process. Conclusions Dyschromatopsia is an increasingly common disease in the world. The method we developed can diagnose dyschromatopsia. The algorithm also develops a metric scale for recognizing the degree of severity. The algorithm can be used independently by specilized and non-specilized people. In addition, the algorithm can be integrated with Machine Learning techniques to create a customized eye retrainer based on the plasticity and adaptability of neural tissue

Electrocardiogram pattern recognition and analysis based on artificial neural networks and support vector machines: a review.

Computer systems for Electrocardiogram (ECG) analysis support the clinician in tedious tasks (e.g., Holter ECG monitored in Intensive Care Units) or in prompt detection of dangerous events (e.g., ventricular fibrillation). Together with clinical applications (arrhythmia detection and heart rate variability analysis), ECG is currently being investigated in biometrics (human identification), an emerging area receiving increasing attention. Methodologies for clinical applications can have both differences and similarities with respect to biometrics. This paper reviews methods of ECG processing from a pattern recognition perspective. In particular, we focus on features commonly used for heartbeat classification. Considering the vast literature in the field and the limited space of this review, we dedicated a detailed discussion only to a few classifiers (Artificial Neural Networks and Support Vector Machines) because of their popularity; however, other techniques such as Hidden Markov Models and Kalman Filtering will be also mentioned

Bedside communication and management of vital parameters and alarms in care-intensive environments: Simulation model development for the clinical effectiveness analysis of an innovative technology

Background and Objective. The deliberation n.7301 of 31/12/2001 provides for the inclusion of a call system with acoustic and luminous signalling within the minimum equipment of the recovery ward. However, traditional call systems are inefficient since they are based on the following incorrect assumptions: patients and staff are unmoving, information sources are static and assistance is unidirectional. Taking care of a patient involves different figures who should be dynamic and should be able to exchange information. Furthermore, the high number of clinical calls and alarms might be an issue, because on one hand they are essential to fulfil patients' needs, but on the other hand they could cause stress and additional workload on medical staff. Indeed, they sometimes ignore some calls or waste a lot of time on non-urgent requests. In addition, the identification of an alarm and the prompt intervention seems to be more difficult during travelling. An ideal alarm system should have 100% sensitivity and specificity. Nevertheless, the alarms are designed to be extremely sensitive, at the expense of specificity. The alarm fatigue, that is the work overload due to an excessive alarms number exposition, is a critical problem in terms of safety in the current clinical practice because it involves desensitization and alarm loss, causing sometimes even the patient's death. Material and Methods. Therefore, appropriate approaches to notifications should be evaluated, including the effectiveness of mobile wireless technologies: linking patients, staff, data, services and medical devices simplifies communications and workflows. Several issues related to the communication among staff members, between patient and caregiver and to the alarms and vital parameters distribution in care-intensive environments have been analysed, focusing on the clinical effectiveness analysis of an innovative technology to support the Emergency Department of the Azienda Ospedaliera dei Colli activities. Afterwards, we have created a simulation model with Simul8, so that a digital twin reproduces direct and indirect activities in two cases: with and without (What If and As Is model) the aid of the technology. Results and conclusions. The model provides a set of Key Performance Indicators (number of performing activities, average alarm resolution time, waiting time) on which the compensatory aggregation method is applied to elaborate a single final score in both cases. This score is 52,5 in the As Is Model and 80 in the What If model. So, the clinical effectiveness has been demonstrated

Implementing simulation–based approaches for healthcare workflow analysis

The Discrete Event Simulation (DES) approach has become a popular technique for problem solving in healthcare, as it provides a very realistic picture of the actual system. A simulation–based operational paradigm by means of the SIMUL8 software suite was implemented in the Department of Laboratory Medicine (DLM) of the "San Paolo” Hospital in Naples (Italy), as support of the Business Process Management (BPM) methodology, to analyse and improve the performances the current working performances

Serious Games in Autism Spectrum Disorder - An Example of Personalised Design

Over the last decade, several studies evaluated the use of Serious Games as tools to encourage the development of communication, the process of learning, and social behaviour in people with Autism Spectrum Disorder (ASD) alongside traditional therapeutic approaches. The proposed study intends to employ and rate the use of Serious Games to create personalised interactive environments aimed to improve the learning of educational content in children with ASD. In particular, a multidisciplinary team supported the design and development of the serious game to allow a personalised approach

Strumenti di immersive simulation rivolti a persone con Disturbi dello Spettro Autistico

I Disturbi dello Spettro Autistico (Autism Spectrum Disorders – ASD) comprendono un insieme di quadri psicopatologici caratterizzati da diverse difficoltà nelle relazioni intersoggettive, nella comunicazione e nell’inclusione sociale. Diversi studi hanno valutato l’utilizzo di serious games come strumento, da affiancare ai percorsi terapeutici tradizionali, per favorire il potenziamento della comunicazione, del processo di apprendimento, del comportamento sociale e delle abilità psicomotorie in persone con ASD. Lo studio proposto si pone l’obiettivo di adoperare e valutare l’utilizzo di strumenti di immersive simulation per rafforzare e incrementare l’apprendimento di nozioni logico-matematiche elementari in soggetti con ASD. La progettazione e lo sviluppo del serious game sono stati supportati da un team multidisciplinare che ha individuato un gruppo tester e ha determinato gli aspetti essenziali per lo sviluppo dell’applicazione tramite la stesura di un adeguato documento di progettazione. La fase di sviluppo del prototipo è stata supportata dall’utilizzo di Unity come game engine e di 3D Studio Max come software di modellazione 3D. Il prototipo di gioco, sviluppato su più livelli, è stato realizzato per PC ed è attualmente in fase di testing con gli utenti. Dai risultati della prima fase di testing si potrà valutare se siano presenti fattori o elementi da riprogettare per completare lo sviluppo del serious game e avere una prima stima degli effetti in termini di apprendimento e sviluppo di competenze

The Use of FPGA in Drift Chambers for High Energy Physics Experiments

In this chapter, we describe the design of a field programmable gate array (FPGA) board capable of acquiring the information coming from a fast digitization of the signals generated in a drift chambers. The digitized signals are analyzed using an ad hoc real‐time algorithm implemented in the FPGA in order to reduce the data throughput coming from the particle detector

Personalized training via serious game to improve daily living skills in pediatric patients with autism spectrum disorder

The majority of people with Autism Spectrum Disorder (ASD) exhibit difficulties in social communication and behavior, which hinder their learning capability, amid others. Among technological solutions for people with ASD, serious games are frequently used to enhance learning of specific skills and instructional contents. However, because of heterogeneity in applications and game design, few studies have investigated their use in training daily activities. This paper presents a 3D personalized serious game we developed and validated to help ASD patients practice with shopping activities. Personalized training is paramount in people with ASD, thus several elements of this game were personalized to improve engagement and therefore the effectiveness of the virtual training. In order to assess the validity of the game, ten subjects (age 11.9 2.7, 20% female) with ASD played ten sessions of the serious game, once per week. The participants underwent a real-life experience pre- and post-training in a real-life supermarket. Changes in daily living skills among participants were evaluated through specific tools: a form based on the International Classification of Functioning, Disability and Health for Children and Youth; and the Vineland Adaptive Behavior Scale II. Significant improvements (p<0.05) were detected in the main skills trained with the serious game, especially in learning the shopping procedure, directing attention, and problem-solving skills. These findings suggest that personalized serious games can represent a prominent tool to enhance daily living skills, but future work should clinically validate their efficacy