Entity

Time filter

Source Type


Hristoskova A.,Ghent University | Sakkalis V.,University of Crete | Zacharioudakis G.,University of Crete | Tsiknakis M.,Technological Educational Institute of Crete | And 2 more authors.
Sensors (Switzerland) | Year: 2014

A major challenge related to caring for patients with chronic conditions is the early detection of exacerbations of the disease. Medical personnel should be contacted immediately in order to intervene in time before an acute state is reached, ensuring patient safety. This paper proposes an approach to an ambient intelligence (AmI) framework supporting real-time remote monitoring of patients diagnosed with congestive heart failure (CHF). Its novelty is the integration of: (i) personalized monitoring of the patients health status and risk stage; (ii) intelligent alerting of the dedicated physician through the construction of medical workflows on-the-fly; and (iii) dynamic adaptation of the vital signs' monitoring environment on any available device or smart phone located in close proximity to the physician depending on new medical measurements, additional disease specifications or the failure of the infrastructure. The intelligence lies in the adoption of semantics providing for a personalized and automated emergency alerting that smoothly interacts with the physician, regardless of his location, ensuring timely intervention during an emergency. It is evaluated on a medical emergency scenario, where in the case of exceeded patient thresholds, medical personnel are localized and contacted, presenting ad hoc information on the patient's condition on the most suited device within the physician's reach. © 2014 by the authors; licensee MDPI, Basel, Switzerland. Source


Stavrinidis G.,Microelectronics Research Group | Michelakis K.,University of Surrey | Kontomitrou V.,Microelectronics Research Group | Giannakakis G.,Computational Medicine Laboratory | And 5 more authors.
Microelectronic Engineering | Year: 2016

This work demonstrates a novel, simple method for the fabrication of dry Electroencephalogram (EEG) electrodes consisting of arrays of SU8 based microneedles. EEG electrodes fabricated this way will significantly reduce the duration and complexity of the mounting procedure as they eliminate the need for skin preparation and the application of conductive paste. Arrays of polymer based microneedles were designed and then realized using a simple, low cost photolithographic technique. The polymer used for the microneedle fabrication is epoxy based SU-8 and the microneedle array is formed on a glass carrier. A single, "back-side" photolithographic exposure is applied for the formation of sharp and appropriately-sloped microneedles. The resulting needles are cone-shaped and 500 μm in height with a base of 100 μm in diameter and a tip smaller than 30 μm. The microneedles are subsequently covered conformally with a thin film of biocompatible metal (Ag) rendering them suitable for human skin penetration. In addition, human skin penetration did not compromise the mechanical integrity of the microneedles. Initial electrical characterization results from a trial on a healthy human show that the fabricated electrodes provide excellent EEG signal strength presenting low resistivity contact. © 2016 Elsevier B.V. All rights reserved. Source


Kondylakis H.,Computational Medicine Laboratory | Koumakis L.,Computational Medicine Laboratory | Tsiknakis M.,Computational Medicine Laboratory | Tsiknakis M.,Technological Educational Institute of Crete | And 5 more authors.
Smart Innovation, Systems and Technologies | Year: 2013

Medicine is undergoing a revolution that is transforming the nature of healthcare from reactive to preventive. The changes are catalyzed by a new systems approach to disease which focuses on integrated diagnosis, treatment and prevention of disease in individuals. This will replace our current mode of medicine over the coming years with a personalized predictive treatment. While the goal is clear, the path is fraught with challenges. The p-medicine EU project aspires to create an infrastructure that will facilitate this translation from current medical practice to personalized medicine. This Chapter focus on current research activities related to the design and implementation of an intelligent patient empowerment platform and its services. The focus of our work concerns the nature of the interaction between health institutions and individuals, particularly the communicative relation between physicians and patients, the ways of exchanging information, the nature of the information itself and the information assimilation capabilities of the patients. Our practical focus is the domain of cancer patients, whether in normal treatment or participating in clinical trials. The ultimate objective is to implement a smart environment (recommender system) able to act as a decision support infrastructure to support the communication, interaction and information delivery process form the doctor to the patient. A prerequisite of personalized delivery of information and intelligent guidance of the patient into his/her treatment plans is our ability to develop an appropriate and accurate profile of the user. In the p-medicine project we focus on modeling and profiling the psycho-cognitive capabilities of the patient based on questionnaires and other information features and behaviors extracted from a personal health record of the patient. In this chapter we will provide a systematic review of user profiling techniques and approaches and present our results in developing a psycho-cognitive profile of the user/patient. Subsequently we will describe the details and challenges of implementing the recommendation system and services using a combination of methods to counter-balance the intrinsic weaknesses in various algorithmic approaches. We will review solutions that have combined demographic user classes and content-based filters using implicit behavior and explicit preferences, collaborative filtering and demographic or collaborative filtering and knowledge-based filters. Finally, our approach will be fully described, which uses an adaptive user interface for the presentation of the e-consent, an ontology and a semantic web rule language to formally describe patient choices, and a reasoning engine to handle access and personalized delivery of pertinent disease related information. © Springer International Publishing Switzerland 2013. Source


Genitsaridi I.,Computational Medicine Laboratory | Kondylakis H.,Computational Medicine Laboratory | Koumakis L.,Computational Medicine Laboratory | Marias K.,Computational Medicine Laboratory | And 2 more authors.
Procedia Computer Science | Year: 2013

Personal health record (PHR) systems are a constantly evolving area in the field of health information technology which motivates an ongoing research towards their evaluation in several different aspects. In this direction, we present an evaluation study on PHR systems that provides an insight on their current status with regard to functional and technical capabilities and we present our extensions to a specific PHR system. Essentially, we provide a requirement analysis that formulates our composite evaluation model which we use to perform a systems review on numerous available solutions. Then, we present our development efforts towards an intelligent PHR system. © 2013 The Authors. Source


Kondylakis H.,Computational Medicine Laboratory | Kazantzaki E.,Computational Medicine Laboratory | Koumakis L.,Computational Medicine Laboratory | Genitsaridi I.,Computational Medicine Laboratory | And 9 more authors.
ecancermedicalscience | Year: 2014

In an epoch where shared decision making is gaining importance, a patient's commitment to and knowledge about his/her health condition is becoming more and more relevant. Health literacy is one of the most important factors in enhancing the involvement of patients in their care. Nevertheless, other factors can impair patient processing and understanding of health information: psychological aspects and cognitive style may affect the way patients approach, select, and retain information. This paper describes the development and validation of a short and easy to fill-out questionnaire that measures and collects psycho-cognitive information about patients, named ALGA-C. ALGA-C is a multilingual, multidevice instrument, and its validation was carried out in healthy people and breast cancer patients. In addition to the aforementioned questionnaire, a patient profiling mechanism has also been developed. The ALGA-C Profiler enables physicians to rapidly inspect each patient's individual cognitive profile and see at a glance the areas of concern. With this tool, doctors can modulate the language, vocabulary, and content of subsequent discussions with the patient, thus enabling easier understanding by the patient. This, in turn, helps the patient formulate questions and participate on an equal footing in the decision-making processes. Finally, a preview is given on the techniques under consideration for exploiting the constructed patient profile by a personal health record (PHR). Predefined rules will use a patient's profile to personalise the contents of the information presented and to customize ways in which users complete their tasks in a PHR system. This optimises information delivery to patients and makes it easier for the patient to decide what is of interest to him/her at the moment. Copyright: the authors;. Source

Discover hidden collaborations