Artur Rocha

CAALYX: a new generation of location-based services in healthcare

Recent advances in mobile positioning systems and telecommunications are providing the technology needed for the development of location-aware tele-care applications. This paper introduces CAALYX – Complete Ambient Assisted Living Experiment, an EU-funded project that aims at increasing older peoples autonomy and self-confidence by developing a wearable light device capable of measuring specific vital signs of the elderly, detecting falls and location, and communicating automatically in real-time with his/her care provider in case of an emergency, wherever the older person happens to be, at home or outside.

Innovative ICT solutions to improve treatment outcomes for depression: the ICT4Depression project

Depression is expected to be the disorder with the highest disease burden in high-income countries by the year 2030. ICT4Depression (ICT4D) is a European FP7 project, which aims to contribute to the alleviation of this burden by making use of depression treatment and ICT innovations. In this project we developed an ICT-based system for use in primary care that aims to improve access as well as actual care delivery for depressed adults. Innovative technologies within the ICT4D system include 1) flexible self-help treatments for depression, 2) automatic assessment of the patient using mobile phone and web-based communication 3) wearable biomedical sensor devices for monitoring activities and electrophysiological indicators, 4) computational methods for reasoning about the state of a patient and the risk of relapse (reasoning engine) and 5) a flexible system architecture for monitoring and supporting people using continuous observations and feedback via mobile phone and the web. The general objective of the ICT4D project is to test the feasibility and acceptability of the ICT4D system within a pilot study in the Netherlands and in Sweden during 2012 and 2013.

Integration of a suite of sensors in a wireless health sensor platform

In this paper we discuss the development and clinical evaluation of a wireless platform for health signs sensing. The sensors measure physical activity, ECG, blood oxygen saturation, temperature and respiratory rate. An important aspect of the approach is that the sensors are integrated into one waist-worn device. A mobile phone collects data from this device and uses data fusion in the scope of a decision support system to trigger additional measurements, classify health conditions or schedule future observations. In these decisions, the users current physical activity plays an important role as the validity of many health signs measurements is strongly related to physical activity. Due to the integration of the sensors and the use of data fusion it is possible to accurately identify health risks and to react promptly. During clinical trials, for which proper ethical approval was obtained, the system was used by healthy elderly volunteers in Limerick (Ireland) and Ancona (Italy). Results of these trials are also discussed in this paper.

M-GIS: Mobile and interoperable access to geographic information

This paper describes an architecture which can be used to access geographic information from mobile devices with limited display and processing characteristics, such as Personal Digital Assistants (PDA) or Mobile Phones. The information may come from different sources leading to an interoperable solution.

Interoperable geographic information services to support crisis management

In this article we focus on interoperable geographic information (GI) services from the crisis management perspective. Based on Open Geospatial Consortium [10] standards and initiatives, we present the building blocks of the interoperable solution for supporting crisis management that is proposed as a result of the EU sponsored project, MEDSI [1]. In particular, we focus on the application and operationalization of several OGC standards, some adopted and some still under discussion, such as WMS, WFS, WMC, SLD and SMS, as well as their integration and cooperation within a single software framework.

ICT4Depression: Service oriented architecture applied to the treatment of depression

FP7 ICT4Depression project aims at providing a set of tools to further improve both patient outcome and increase of access to treatment of the patients suffering from major depression. This article describes the Information Systems (IS) architecture used in the project. ICT4Depression uses a service oriented architecture as means of bringing together different kinds of information concerning the patient, the therapeutic modules he is advised to follow and the sensors used to assess his status.

SINUP: Using GIS to Support E-Democracy

SINUP consists of a geographical information system whose purpose is to store, in a coherent manner, data resulting from key activities of Oporto local authority, allowing to better structure the knowledge about the urban reality. In the possession of such knowledge, and with the revision of Oporto’s Municipal Master Plan taking place soon, the municipality is making an effort to develop an electronic citizen service that will allow a large number of citizens to consult it, and more important, participate in its public discussion prior to approval thus creating a major instrument of e-democracy in Oporto’s municipality.

Enriching Mental Health Mobile Assessment and Intervention with Situation Awareness

Current mobile devices allow the execution of sophisticated applications with the capacity for identifying the user situation, which can be helpful in treatments of mental disorders. In this paper, we present SituMan, a solution that provides situation awareness to MoodBuster, an ecological momentary assessment and intervention mobile application used to request self-assessments from patients in depression treatments. SituMan has a fuzzy inference engine to identify patient situations using context data gathered from the sensors embedded in mobile devices. Situations are specified jointly by the patient and mental health professional, and they can represent the patient’s daily routine (e.g., “studying”, “at work”, “working out”). MoodBuster requests mental status self-assessments from patients at adequate moments using situation awareness. In addition, SituMan saves and displays patient situations in a summary, delivering them for consultation by mental health professionals. A first experimental evaluation was performed to assess the user satisfaction with the approaches to define and identify situations. This experiment showed that SituMan was well evaluated in both criteria. A second experiment was performed to assess the accuracy of the fuzzy engine to infer situations. Results from the second experiment showed that the fuzzy inference engine has a good accuracy to identify situations.

Efficient Delivery of Forecasts to a Nautical Sports Mobile Application with Semantic Data Services

Weather and sea-related forecasts provide crucial insights for the practice of nautical sports such as surf and kite surf, and mobile devices are appropriate interfaces for the visualization of meteorology and operational oceanography data. Data are collected and processed by several agencies and are often obtained from forecast models. Their use requires adaptation and refinement prior to visualisation. We describe a set of semantic data services using standard common vocabularies and interoperable interfaces following the recommendations of the INSPIRE directive. NautiCast, a mobile application for forecast delivery illustrates the adaptation of data at two levels: 1) semantic, with the integration of data from different sources via standard vocabularies, and 2) syntactic, with the manipulation of the spacial and temporal resolution of data to get effective mobile communication.

Improvements to efficient retrieval of very large temporal datasets with the TravelLight method

A considerable number of domains deal with large and complex volumes of temporal data. The management of these volumes, from capture, storage, search, transfer, analysis and visualization, still provides interesting challenges. One critical task is the efficient retrieval of data (raw data or intermediate results from analytic tools). Previous work proposed the TravelLight method which reduced the turnaround time and improved interactive retrieval of data from large temporal datasets by exploring the temporal consistency of records in a database. In this work we propose improvements to the method by adopting a new paradigm focused in the management of time intervals instead of solely in data items. A major advantage of this paradigm shift is to enable the separation of the method implementation from any particular temporal data source, as it is autonomous and efficient in the management of retrieved data. Our work demonstrates that the overheads introduced by the new paradigm are smaller than prior overall overheads, further reducing the turnaround time. Reported results concern experiments with a temporally linear navigation across two datasets of one million items. With the obtained results it is possible to conclude that the improvements presented in this work further reduce turnaround time thus enhancing the response of interactive tasks over very large temporal datasets.