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About

About

He is a senior researcher at INESC TEC, where he works since 1998. Current research interests are the semantic sensor Web (IoT), geospatial semantic Web, service ecosystems and e-Science infrastructures.

From October 1996 to December 1997, he was an associate member of CERN - European
Laboratory for High Energy Physics, IT Division/Web Office.

He has participated in several European projects, namely GISEDI (FP4), MEDSI (FP6), CAALYX (FP6), ICT4Depression (FP7), E-COMPARED (FP7) and RECAP (H2020), mostly as responsible for the system's architecture and platform implementation or as technical coordinator.

He also participates in the implementation of the RAIA Observatory, C4G which is the Portuguese node of EPOS, in the EEA Grant STOP Depression, in the EEA Grant SeaBioData, in Interreg MarRisk and FCT iCare4Depression.

Interest
Topics
Details

Details

011
Publications

2017

Screening and evaluation platform for depression and suicidality in primary healthcare

Authors
Cassola, F; Costa, A; Henriques, R; Rocha, A; Sousa, M; Gomes, P; Ferreira, T; Cunha, C; Salgado, J;

Publication
ICT4AWE 2017 - Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health

Abstract
This work presents a screening and evaluation platform for depression and suicidality that has been tested in the scope of primary healthcare. The main objective is to improve the efficiency and effectiveness of screening processes. A web-based, decision support platform was provided for qualified healthcare professionals. The platform provides several assessment tools for patient evaluation and monitoring of their treatment, along with follow up appointment management. A preliminary evaluation process was carried out to understand the health professional's satisfaction. This revealed there was general satisfaction with its integrated functions and all the provided methods of assessment. In conclusion, the project sustains the goal of improving the treatment outcomes for clinical depression by refining the screening methods and consequently increase the screening effectiveness and efficiency.

2017

Predicting short term mood developments among depressed patients using adherence and ecological momentary assessment data

Authors
Mikus, A; Hoogendoorn, M; Rocha, A; Gama, J; Ruwaard, J; Riper, H;

Publication
Internet Interventions

Abstract

2017

Enriching Mental Health Mobile Assessment and Intervention with Situation Awareness

Authors
Teles, AS; Rocha, A; da Silva e Silva, FJDE; Lopes, JC; O'Sullivan, D; Van de Ven, P; Endler, M;

Publication
SENSORS

Abstract
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.

2017

ULTEMAT: A mobile framework for smart ecological momentary assessments and interventions

Authors
van de Ven, P; O'Brien, H; Henriques, R; Klein, M; Msetfi, R; Nelson, J; Rocha, A; Ruwaard, J; O'Sullivan, D; Riper, H;

Publication
Internet Interventions

Abstract
In this paper we introduce a new Android library, called ULTEMAT, for the delivery of ecological momentary assessments (EMAs) on mobile devices and we present its use in the MoodBuster app developed in the H2020 E-COMPARED project. We discuss context-aware, or event-based, triggers for the presentation of EMAs and discuss the potential they have to improve the effectiveness of mobile provision of mental health interventions as they allow for the delivery of assessments to the patients when and where these are most appropriate. Following this, we present the abilities of ULTEMAT to use such context-aware triggers to schedule EMAs and we discuss how a similar approach can be used for Ecological Momentary Interventions (EMIs). © 2017

2016

Measuring littoral surface currents with low-cost wave drifters

Authors
Diogo, M; Bruno, L; Artur, R; António, DS;

Publication
Frontiers in Marine Science

Abstract

Supervised
thesis

2016

Platform for monitoring and treat depression

Author
José Pedro Alves Ornelas

Institution
UP-FCUP