14 research outputs found
Citclops: Data Interpretation and Knowledge-based Systems Integration
Measuring the optical properties of water bodies (as indicators of, e.g., sewage impact, dissolved organic matter, sediment load or gross biological activity) is a way to assess their environmental status. The Citclops European project, in 2012-2015, developed systems to retrieve and use data on natural-water colour, transparency and fluorescence, using low-cost sensors combined with contextual information, taking into account existing experiences. This paper describes the general interpretation of data and delivery of information as carried out via the development of a decision support system named 'Citclops Data Explorer' and available from the main portal of the project
Towards Argumentation-based Recommendations for Personalised Patient Empowerment
Patient empowerment is a key issue in healthcare. Approaches to increase patient empowerment encompass patient self-management programs. In this paper we present ArgoRec, a recommender system that exploits argumentation for leveraging explanatory power and natural language interactions so as to improve patients' user experience and quality of recommendations. ArgoRec is part of a great effort concerned with supporting complex chronic patients in, for instance, their daily life activities after hospitalisation, pursued within the CONNECARE project by following a co-design approach to define a comprehensive Self-Management System
Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy
Background: Patients suffering obstructive sleep apnea are mainly treated with continuous positive airway pressure
(CPAP). Although it is a highly effective treatment, compliance with this therapy is problematic to achieve with serious
consequences for the patients’ health. Unfortunately, there is a clear lack of clinical analytical tools to support the early
prediction of compliant patients.
Methods: This work intends to take a further step in this direction by building compliance classifiers with CPAP
therapy at three different moments of the patient follow-up, before the therapy starts (baseline) and at months 1 and
3 after the baseline.
Results: Results of the clinical trial shows that month 3 was the time-point with the most accurate classifier reaching
an f1-score of 87% and 84% in cross-validation and test. At month 1, performances were almost as high as in month 3
with 82% and 84% of f1-score. At baseline, where no information of patients’ CPAP use was given yet, the best
classifier achieved 73% and 76% of f1-score in cross-validation and test set respectively. Subsequent analyzes carried
out with the best classifiers of each time point revealed baseline factors (i.e. headaches, psychological symptoms,
arterial hypertension and EuroQol visual analog scale) closely related to the prediction of compliance independently
of the time-point. In addition, among the variables taken only during the follow-up of the patients, Epworth and the
average nighttime hours were the most important to predict compliance with CPAP.
Conclusions: Best classifiers reported high performances after one month of treatment, being the third month when
significant differences were achieved with respect to the baseline. Four baseline variables were reported relevant for
the prediction of compliance with CPAP at each time-point. Two characteristics more were also highlighted for the
prediction of compliance at months 1 and 3.This work is part of the myOSA project (RTC-2014-3138-1), funded by the Spanish Ministry of Economy and Competitiveness (Ministerio de EconomĂa y Competitividad) under the framework “Retos-ColaboraciĂłn”, State Scientific and Technical Research and Innovation Plan 2013-2016. The study was also partially funded by the European Community under “H2020-EU.3.1. – Societal Challenges – Health, demographic change and well-being” programme, project grant agreement number 689802 (CONNECARE)
Protocol for regional implementation of collaborative self-management services to promote physical activity
Background: Chronic diseases are generating a major health and societal burden worldwide. Healthy lifestyles, including physical activity (PA), have proven efficacy in the prevention and treatment of many chronic conditions. But, so far, national PA surveillance systems, as well as strategies for promotion of PA, have shown low impact. We hypothesize that personalized modular PA services, aligned with healthcare, addressing the needs of a broad spectrum of individual profiles may show cost-effectiveness and sustainability. Methods: The current manuscript describes the protocol for regional implementation of collaborative self-management services to promote PA in Catalonia (7.5 M habitants) during the period 2017-2019. The protocols of three implementation studies encompassing a broad spectrum of individual needs are reported. They have a quasi-experimental design. That is, a non-randomized intervention group is compared to a control group (usual care) using propensity score methods wherein age, gender and population-based health risk assessment are main matching variables. The principal innovations of the PA program are: i) Implementation of well-structured modular interventions promoting PA; ii) Information and communication technologies (ICT) to facilitate patient accessibility, support collaborative management of individual care plans and reduce costs; and iii) Assessment strategies based on the Triple Aim approach during and beyond the program deployment. Discussion: The manuscript reports a precise roadmap for large scale deployment of community-based ICT-supported integrated care services to promote healthy lifestyles with high potential for comparability and transferability to other sites. Trial registration: This study protocol has been registered at ClinicalTrials.org ( NCT02976064 ). Registered November 24th, 2016
Towards an Intelligent Monitoring System for Patients with Obstrusive Sleep Apnea
Due to the growing incidence of chronic diseases and aging populations, the pressure to control costs and the expectations of continuous improvements in the quality of service have increased the need to understand how healthcare is provided and to determine whether cost-effective improvements to care practices can be made. In the case of people suffering Obstructive Sleep Apnea, patients using self-administer nasal Continuous Positive Airway Pressure (CPAP) may receive information on the treatment only once they go to a visit with the lung specialist. In this paper, we propose an IoT-based Intelligent Monitoring System that relies on machine learning to achieve a threefold goal: (1) it is aimed at early detecting compliance in order to predict CPAP usage; (2) it monitors the actual adherence degree to the treatment to keep informed both the patient and the lung specialists; and (3) it sends recommendations to the patient to empower her/him and to better follow up
Citizens’ Observatories in coastal environments: using innovative technologies (DIY instruments and data sonification) for engaging volunteers
First International ECSA Conference 2016. Citizen Science - Innovation in Open Science, Society and Policy, 19-21 May 2016, Berlin.-- 2 pagesPeer Reviewe
Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy
Protocol for regional implementation of collaborative self-management services to promote physical activity
Abstract Background Chronic diseases are generating a major health and societal burden worldwide. Healthy lifestyles, including physical activity (PA), have proven efficacy in the prevention and treatment of many chronic conditions. But, so far, national PA surveillance systems, as well as strategies for promotion of PA, have shown low impact. We hypothesize that personalized modular PA services, aligned with healthcare, addressing the needs of a broad spectrum of individual profiles may show cost-effectiveness and sustainability. Methods The current manuscript describes the protocol for regional implementation of collaborative self-management services to promote PA in Catalonia (7.5 M habitants) during the period 2017–2019. The protocols of three implementation studies encompassing a broad spectrum of individual needs are reported. They have a quasi-experimental design. That is, a non-randomized intervention group is compared to a control group (usual care) using propensity score methods wherein age, gender and population-based health risk assessment are main matching variables. The principal innovations of the PA program are: i) Implementation of well-structured modular interventions promoting PA; ii) Information and communication technologies (ICT) to facilitate patient accessibility, support collaborative management of individual care plans and reduce costs; and iii) Assessment strategies based on the Triple Aim approach during and beyond the program deployment. Discussion The manuscript reports a precise roadmap for large scale deployment of community-based ICT-supported integrated care services to promote healthy lifestyles with high potential for comparability and transferability to other sites. Trial registration This study protocol has been registered at ClinicalTrials.org (NCT02976064). Registered November 24th, 2016
Autonomous rehabilitation at stroke patients home for balance and gait: safety, usability and compliance of a virtual reality system
New technologies, such as telerehabilitation and gaming devices offer the possibility for patients to train at home. This opens the challenge of safety for the patient as he is called to exercise neither with a therapist on the patients' side nor with a therapist linked remotely to supervise the sessions