Charalampos Tsirmpas

An indoor navigation system for visually impaired and elderly people based on Radio Frequency Identification (RFID)

One of the most challenging limitations for the elderly and/or the visually impaired people is the inability of self-navigation in unfamiliar indoor environments. Numerous existing indoor navigation systems have been proposed in order to solve such problems. However, these papers do not adequately examine the effectiveness of the systems in real time trials and are faced with a variety of technical and usability problems. In our paper we present a unique and elegant architecture of an indoor navigation system as an integrated and tested system in real time. This solution enables the localization of the user, as well as the navigation considering scenarios that the user might follow and suggests guidelines for self- navigation. To evaluate the feasibility of the proposed architecture we carried out experimental scenarios to prove that the system proposed is suitable enough to guide elderly people through an unknown built environment.

A New Method for Profile Generation in an Internet of Things Environment: An Application in Ambient-Assisted Living

Ambient-assisted living (AAL) is currently one of the important research and development areas, where accessibility, usability, and learning play a major role and where future interfaces are an important concern for applied engineering. The general goal of AAL solutions is to apply ambient intelligence technology to enable people with specific demands, e.g., handicapped or elderly, to live in their preferred environment longer. The term “Internet of Things” (IoT) is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. In this context, we propose a new methodology based on self organizing maps (SOMs) and fuzzy C-means (FCM) algorithms for profile generation as regards the activities of the user and their correlation with the available sensors. Moreover, we utilize the provided context to assign the generated profiles to more contextually complex activities. Our methodology is being evaluated into an AAL structure equipped with several sensors. More precisely, we assess the proposed method in a data set generated by accelerometers and its performance over a number of everyday activities.

E-Health towards ecumenical framework for personalized medicine via Decision Support System

The purpose of the present manuscript is to present the advances performed in medicine using a Personalized Decision Support System (PDSS). The models used in Decision Support Systems (DSS) are examined in combination with Genome Information and Biomarkers to produce personalized result for each individual. The concept of personalize medicine is described in depth and application of PDSS for Cardiovascular Diseases (CVD) and Type-1 Diabetes Mellitus (T1DM) are analyzed. Parameters extracted from genes, biomarkers, nutrition habits, lifestyle and biological measurements feed DSSs, incorporating Artificial Intelligence Modules (AIM), to provide personalized advice, medication and treatment.

Smart adaptable system for older adults' Daily Life Activities Management - The ABLE platform.

In this paper we propose a system (ABLE) that will act as the main platform for a number of low-cost, mature technologies that will be integrated in order to create a dynamically adaptive Daily Life Activities Management environment in order to facilitate the everyday life of senior (but not exclusively) citizens at home. While the main target group of ABLEs users is the ageing population its use can be extended to all people that are vulnerable or atypical in body, intellect or emotions and are categorized by society as disabled. The classes of assistive products that are well defined in the international standard, ISO9999 such as assistive products for personal medical treatment, personal care and protection, communication, information and reaction and for personal mobility, will be easily incorporated in our proposed platform. Furthermore, our platform could integrate and implement the above classes under several service models that will be analyzed further.

Information Extraction, Matching and Reporting for Medical Devices Vigilance

Medical devices play a vital role in the delivery of high quality healthcare with their numbers increasing exponentially during the past fifty years. Although recent technological advancements have led to much more reliable and safer Medical Devices (MDs), potential risks of failure and the associated adverse incidents cannot be ignored. To create a safer environment for the patient in terms of technology, it is necessary to provide rapid and accurate information on adverse events, in order to avoid their repetition. The traditional approach of MD Vigilance based only on official user reports of adverse incidents has been proven inadequate today. A modern approach, also used in this work, to the problem is based on the introduction of additional means, such as data mining, extraction, standardization and codification of the information, from different direct and indirect sources worldwide, and its systematic classification and archiving in dedicated databases. The aim is to timely extract information on potentially hazardous MDs and to make it available where appropriate.

Bayesian networks to support the management of patients with ASCUS/LSIL pap tests

In the majority of cases, cervical cancer (CxCa) develops as a result of underestimated abnormalities in the Pap test. Nowadays, there are ancillary molecular biology techniques providing important information related to CxCa and the Human Papillomavirus (HPV) natural history, including HPV DNA test, HPV mRNA tests and immunocytochemistry tests. However, these techniques have their own performance, advantages and limitations, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this paper we present a risk assessment model based on a Bayesian Network which, by combining the results of Pap test and ancillary tests, may identify women at true risk of developing cervical cancer and support the management of patients with ASCUS or LSIL cytology. The model, following the paradigm of other implemented systems, can be integrated into existing platforms and be available on mobile terminals for anytime/anyplace medical consultation.

An Internet of Things platform architecture for supporting ambient assisted living environments

Internet of Things (IoT) is the logical further development of todays Internet, enabling a huge amount of devices to communicate, compute, sense and act. IoT sensors placed in Ambient Assisted Living (AAL) environments, enable the context awareness and allow the support of the elderly in their daily routines, ultimately allowing an independent and safe lifestyle. The vast amount of data that are generated and exchanged between the IoT nodes require innovative context modeling approaches that go beyond currently used models. Current paper presents and evaluates an open interoperable platform architecture in order to utilize the technical characteristics of IoT and handle the large amount of generated data, as a solution to the technical requirements of AAL applications.

An ensemble feature ranking framework for the assessment of the efficacy of cervical cancer detection tests and human papillomavirus genotypes in the detection of high-grade cervical intraepithelial neoplasia and cervical carcinoma

In most cases, cervical cancer (CxCa) develops as a result of underestimated abnormalities present in cytology via the test Papanicolaou (Pap test). Although it is the sole test that has proved its value for cancer prevention, Pap test is prone to human errors as it is performed via the microscope and requires skilled personnel. Consequently, molecular techniques have emerged in the recent years, aiming to replace Pap test or support the diagnosis as ancillary tests. These include DNA micro-arrays identifying Human Papillomavirus (HPV) subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. These techniques are either highly sensitive or highly specific, but not both at the same time, thus no perfect method is available today. Moreover, most of the published studies compare two tests against each other, which, however, are using different population study groups, therefore it is questionable if the results can be used to perform a direct comparison between the available tests. In this paper, we adopt a sophisticated approach to assess the value of several well-known and widely applied CxCa tests in detecting high-grade cervical intraepithelial neoplasia and CxCa (CIN2+), by employing an Ensemble Feature Ranking framework. Applying the proposed framework we managed to directly compare and rank the studied CxCa tests and several HPV genotypes according to their efficacy in detecting CIN2+ lesions. The results suggest that HPV mRNA tests perform better than HPV DNA testing for the triage of abnormal Pap tests. Such findings may guide cytopathologists in a step by step basis to decide which tests to perform following an abnormal Pap test, in order to decrease uncertainty, improve accuracy and reduce time to diagnosis and resources.

Radio Frequency Identification (RFID) enhanced indoor navigation framework for seniors

One of the most challenging limitations for the elderly and/or the visually impaired people is the inability of self-navigation in unfamiliar indoor environments. Numerous existing indoor navigation systems have been proposed in order to solve such problems. However, these papers do not adequately examine the effectiveness of the systems in real time trials and are faced with a variety of technical and usability problems. In our paper, we present a unique and elegant architecture of an indoor navigation system as an integrated and tested system in real time. This solution enables the localization of the user, as well as the navigation, considering scenarios that the user might follow and suggests guidelines for self-navigation.