136 research outputs found

    Advanced multi-sensor platform for chronic disease home monitoring

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    Nowadays chronic diseases affect an ever-growing segment of population in developed countries; and the management of such kind of diseases requires a huge amount of resources. Chronic Heart Failure, Chronic Obstructive Pulmonary Disease, Diabetes, etc. are the main causes of hospitalization for elderly people, and considering the general aging of population this may lead sustainability problems in the near future. In the last years, clinicians and administrators have identified the telemedicine as strategy to improve the patient management, ensuring both a decreasing of hospital admissions and improving the patient's quality of life. This paper presents a complete system for the management of the healthcare information related to the chronic patient treatment, integrating three main points: a configurable multi-sensor platform for the acquisition and transmission of vital signs, a dedicated server for the provisioning of centralized telemedicine services and the possibility of synchronizing with the electronic health record

    Strategic Intelligence Monitor on Personal Health Systems (SIMPHS): Report on Typology/Segmentation of the PHS Market

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    This market segmentation reports for Personal Health Systems (PHS) describes the methodological background and illustrates the principles of classification and typology regarding different fragments forming this market. It discusses different aspects of the market for PHS and highlights challenges towards a stringent and clear-cut typology or defining market segmentation. Based on these findings a preliminary hybrid typology and indications and insights are created in order to be used in the continuation of the SIMPHS project. It concludes with an annex containing examples and cases studies.JRC.DDG.J.4-Information Societ

    PRESENT AND FUTURE PERVASIVE HEALTHCARE METHODOLOGIES: INTELLIGENT BODY DEVICES, PROCESSING AND MODELING TO SEARCH FOR NEW CARDIOVASCULAR AND PHYSIOLOGICAL BIOMARKERS

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    The motivation behind this work comes from the area of pervasive computing technologies for healthcare and wearable healthcare IT systems, an emerging field of research that brings in revolutionary paradigms for computing models in the 21st century. The aim of this thesis is focused on emerging personal health technologies and pattern recognition strategies for early diagnosis and personalized treatment and rehabilitation for individuals with cardiovascular and neurophysiological diseases. Attention was paid to the development of an intelligent system for the automatic classification of cardiac valve disease for screening purposes. Promising results were reported with the possibility to implement a new screening strategy for the diagnosis of cardiac valve disease in developing countries. A novel assistive architecture for the elderly able to non-invasively assess muscle fatigue by surface electromyography using wireless platform during exercise with an ergonomic platform was presented. Finally a wearable chest belt for ECG monitoring to investigate the psycho-physiological effects of the autonomic system and a wearable technology for monitoring of knee kinematics and recognition of ambulatory activities were characterized to evaluate the reliability for clinical purposes of collected data. The potential impact in the clinical arena of this research would be extremely important, since promising data show how such emerging personal technologies and methodologies are effective in several scenarios to early screening and discovery of novel diagnostic and prognostic biomarkers

    Strategic Intelligence Monitor on Personal Health Systems (SIMPHS): Market Structure and Innovation Dynamics

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    Personal Health Systems (PHS) and Remote Patient Monitoring and Treatment (RMT) have the potential to alter the way healthcare is provided by increasing the quantity and quality of care. This report explores the current status of PHS and, more specifically of the RMT market in Europe. It addresses the question of how these technologies can contribute facing some of the challenges standing in front of the European healthcare delivery systems causes by higher demand pressures through chronic diseases and demographic change combined with diminishing resources for health care. An uptake and diffusion of these services would potentially lead to benefits through a reduction in death rates, and avoid recurring hospitalisation in a cost-effective manner. Yet the report identifies different categories of barriers hampering a full deployment of RMT in Europe. In the concluding part the reports provides a number of tentative policy options specifically aimed at fostering EU-wide deployment of RMT/PHS.JRC.DDG.J.4-Information Societ

    Embedded computing systems design: architectural and application perspectives

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    Questo elaborato affronta varie problematiche legate alla progettazione e all'implementazione dei moderni sistemi embedded di computing, ponendo in rilevo, e talvolta in contrapposizione, le sfide che emergono all'avanzare della tecnologia ed i requisiti che invece emergono a livello applicativo, derivanti dalle necessità degli utenti finali e dai trend di mercato. La discussione sarà articolata tenendo conto di due punti di vista: la progettazione hardware e la loro applicazione a livello di sistema. A livello hardware saranno affrontati nel dettaglio i problemi di interconnettività on-chip. Aspetto che riguarda la parallelizzazione del calcolo, ma anche l'integrazione di funzionalità eterogenee. Sarà quindi discussa un'architettura d'interconnessione denominata Network-on-Chip (NoC). La soluzione proposta è in grado di supportare funzionalità avanzate di networking direttamente in hardware, consentendo tuttavia di raggiungere sempre un compromesso ottimale tra prestazioni in termini di traffico e requisiti di implementazioni a seconda dell'applicazione specifica. Nella discussione di questa tematica, verrà posto l'accento sul problema della configurabilità dei blocchi che compongono una NoC. Quello della configurabilità, è un problema sempre più sentito nella progettazione dei sistemi complessi, nei quali si cerca di sviluppare delle funzionalità, anche molto evolute, ma che siano semplicemente riutilizzabili. A tale scopo sarà introdotta una nuova metodologia, denominata Metacoding che consiste nell'astrarre i problemi di configurabilità attraverso linguaggi di programmazione di alto livello. Sulla base del metacoding verrà anche proposto un flusso di design automatico in grado di semplificare la progettazione e la configurazione di una NoC da parte del designer di rete. Come anticipato, la discussione si sposterà poi a livello di sistema, per affrontare la progettazione di tali sistemi dal punto di vista applicativo, focalizzando l'attenzione in particolare sulle applicazioni di monitoraggio remoto. A tal riguardo saranno studiati nel dettaglio tutti gli aspetti che riguardano la progettazione di un sistema per il monitoraggio di pazienti affetti da scompenso cardiaco cronico. Si partirà dalla definizione dei requisiti, che, come spesso accade a questo livello, derivano principalmente dai bisogni dell'utente finale, nel nostro caso medici e pazienti. Verranno discusse le problematiche di acquisizione, elaborazione e gestione delle misure. Il sistema proposto introduce vari aspetti innovativi tra i quali il concetto di protocollo operativo e l'elevata interoperabilità offerta. In ultima analisi, verranno riportati i risultati relativi alla sperimentazione del sistema implementato. Infine, il tema del monitoraggio remoto sarà concluso con lo studio delle reti di distribuzione elettrica intelligenti: le Smart Grid, cercando di fare uno studio dello stato dell'arte del settore, proponendo un'architettura di Home Area Network (HAN) e suggerendone una possibile implementazione attraverso Commercial Off the Shelf (COTS)

    An Integrated Approach for the Monitoring of Brain and Autonomic Response of Children with Autism Spectrum Disorders during Treatment by Wearable Technologies

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    Autism Spectrum Disorders (ASD) are associated with physiological abnormalities, which are likely to contribute to the core symptoms of the condition. Wearable technologies can provide data in a semi-naturalistic setting, overcoming the limitations given by the constrained situations in which physiological signals are usually acquired. In this study an integrated system based on wearable technologies for the acquisition and analysis of neurophysiological and autonomic parameters during treatment is proposed and an application on five children with ASD is presented. Signals were acquired during a therapeutic session based on an imitation protocol in ASD children. Data were analyzed with the aim of extracting quantitative EEG (QEEG) features from EEG signals as well as heart rate and heart rate variability (HRV) from ECG. The system allowed evidencing changes in neurophysiological and autonomic response from the state of disengagement to the state of engagement of the children, evidencing a cognitive involvement in the children in the tasks proposed. The high grade of acceptability of the monitoring platform is promising for further development and implementation of the tool. In particular if the results of this feasibility study would be confirmed in a larger sample of subjects, the system proposed could be adopted in more naturalistic paradigms that allow real world stimuli to be incorporated into EEG/psychophysiological studies for the monitoring of the effect of the treatment and for the implementation of more individualized therapeutic programs

    Automatic risk evaluation in elderly patients based on Autonomic Nervous System assessment

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    Dysfunction of Autonomic Nervous System (ANS) is a typical feature of chronic heart failure and other cardiovascular disease. As a simple non-invasive technology, heart rate variability (HRV) analysis provides reliable information on autonomic modulation of heart rate. The aim of this thesis was to research and develop automatic methods based on ANS assessment for evaluation of risk in cardiac patients. Several features selection and machine learning algorithms have been combined to achieve the goals. Automatic assessment of disease severity in Congestive Heart Failure (CHF) patients: a completely automatic method, based on long-term HRV was proposed in order to automatically assess the severity of CHF, achieving a sensitivity rate of 93% and a specificity rate of 64% in discriminating severe versus mild patients. Automatic identification of hypertensive patients at high risk of vascular events: a completely automatic system was proposed in order to identify hypertensive patients at higher risk to develop vascular events in the 12 months following the electrocardiographic recordings, achieving a sensitivity rate of 71% and a specificity rate of 86% in identifying high-risk subjects among hypertensive patients. Automatic identification of hypertensive patients with history of fall: it was explored whether an automatic identification of fallers among hypertensive patients based on HRV was feasible. The results obtained in this thesis could have implications both in clinical practice and in clinical research. The system has been designed and developed in order to be clinically feasible. Moreover, since 5-minute ECG recording is inexpensive, easy to assess, and non-invasive, future research will focus on the clinical applicability of the system as a screening tool in non-specialized ambulatories, in order to identify high-risk patients to be shortlisted for more complex investigations

    Remote Powering and Communication of Implantable Biosensors Through Inductive Link

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    Nowadays there is an increasing interest in the field of implantable biosensors. The possibility of real-time monitoring of the human body from inside paves the way to a large number of applications and offers wide opportunities for the future. Within this scenario, the i-IronIC project aims to develop an implantable, low cost, health-care device for real-time monitoring of human metabolites. The contribution of this research work to the i-IronIC project consists of the design and realization of a complete platform to provide power, data communication and remote control to the implantable biosensor. High wearability of the transmitting unit, low invasivity of the implanted electronics, integration of the power management module within the sensor, and a reliable communication protocol with portable devices are the key points of this platform. The power is transmitted to the implanted sensor by exploiting an inductive link. Simulations have been performed to check the effects of several variables on the link performance. These simulations have finally confirmed the possibility to operate in the low megahertz range, where tissue absorption is minimum, even if a miniaturized receiving inductor is used. A wearable patch has been designed to transmit power through the body tissues by driving an external inductor. The same inductive link is used to achieve bidirectional data communication with the implanted device. The patch, named IronIC, is powered by lithium-ion polymer batteries and can be remotely controlled by means of a dedicated Android application running on smartphones and tablets. Long-range communication between the patch and portable devices is performed by means of Bluetooth protocol. Different typologies of receiving inductors have been designed to minimize the size of the implantable device and reduce the discomfort of the patience. Multi-layer, printed spiral inductors and microfabricated spiral inductors have been designed, fabricated and tested. Both the approaches involve a sensibly smaller size, as compared to classic “pancake” inductors used for remote powering. Furthermore, the second solution enables the realization of the receiving inductor directly on the silicon substrate hosting the sensor, thus involving a further miniaturization of the implanted device. An integrated power module has been designed and fabricated in 0.18 μm CMOS technology to perform power management and data communication with the external patch. The circuit, to be merged with the sensor readout circuit, consists of an half-wave voltage rectifier, a low-dropout regulator, an amplitude demodulator and a load modulator. The module receives the power from the implanted inductor and provides a stable voltage to the sensor readout circuit. Finally, the amplitude demodulator and the load modulator enable short-range communication with the patch

    Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

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    Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197
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