Fernando Aparicio

BioAnnote: A software platform for annotating biomedical documents with application in medical learning environments

Automatic term annotation from biomedical documents and external information linking are becoming a necessary prerequisite in modern computer-aided medical learning systems. In this context, this paper presents BioAnnote, a flexible and extensible open-source platform for automatically annotating biomedical resources. Apart from other valuable features, the software platform includes (i) a rich client enabling users to annotate multiple documents in a user friendly environment, (ii) an extensible and embeddable annotation meta-server allowing for the annotation of documents with local or remote vocabularies and (iii) a simple client/server protocol which facilitates the use of our meta-server from any other third-party application. In addition, BioAnnote implements a powerful scripting engine able to perform advanced batch annotations.

Big Data and IoT for Chronic Patients Monitoring

Recent data of the European Union reveals that the main chronic pathologies are the Cardiovascular Disease (CVD), the main cause of death in Europe, and respiratory diseases, specially the Chronic Obstructive Pulmonary Disease (COPD). Each year CVD causes over 4 million deaths in Europe alone and over 1.9 million deaths in the European Union (EU). According to the WHO (World Health Organization), in 2030 COPD will be the third leading cause of death, and the first cause of sanitary costs in Europe, due to the profiles of the expenses in health sector and the long time expenses by age groups and their important associate morbidity. New medical applications based on remote monitoring can help treat those chronic diseases but significantly will increase the volume of health information to manage, including data from medical and biological sensors, being then necessary to process this huge volume of data using techniques from Big Data. In this paper we propose one potential solution for creating those new services, based on Big Data processing and IoT concepts.

Personalized Health Care System with Virtual Reality Rehabilitation and Appropriate Information for Seniors

The concept of the information society is now a common one, as opposed to the industrial society that dominated the economy during the last years. It is assumed that all sectors should have access to information and reap its benefits. Elderly people are, in this respect, a major challenge, due to their lack of interest in technological progress and their lack of knowledge regarding the potential benefits that information society technologies might have on their lives. The Naviga Project (An Open and Adaptable Platform for the Elderly and Persons with Disability to Access the Information Society) is a European effort, whose main goal is to design and develop a technological platform allowing elder people and persons with disability to access the internet and the information society. Naviga also allows the creation of services targeted to social networks, mind training and personalized health care. In this paper we focus on the health care and information services designed on the project, the technological platform developed and details of two representative elements, the virtual reality hand rehabilitation and the health information intelligent system.

A learning support tool with clinical cases based on concept maps and medical entity recognition

The search for truthful health information through Internet is an increasingly complex process due to the growing amount of resources. Access to information can be difficult to control even in environments where the goal pursued is well-defined, as in the case of learning activities with medical students. In this paper, we present a computer tool devised to ease the process of understanding medical concepts from information in clinical case histories. To this end, it automatically constructs concept maps and presents reliable information from different ontologies and knowledge bases. The two main components of the system are an Intelligent Information Access interface and a Concept Map Graph that retrieves medical concepts from a text input, and provides rich information and semantically related concepts. The paper includes a user evaluation of the first component and a systematic assessment for the second component. Results show that our proposal can be efficient and useful for students in a medical learning environment.

Chronic Patients Monitoring Using Wireless Sensors and Big Data Processing

Developed countries are characterized by aging population and economical crisis, so it is desirable to reduce the costs of public and private healthcare systems. It is necessary to streamline the health system resources leading to the development of new medical services based on telemedicine, remote monitoring of chronic patients, personalized health services, new services for dependants, etc. New medical applications based on remote monitoring will significantly increasing the volume of health information to manage, including data from medical and biological sensors, is then necessary process this huge volume of data using techniques from Big Data. In this paper we propose one potential solution for creating those new services, based on Big Data processing and vital signs monitoring.

Security Analysis of an IoT Architecture for Healthcare

Security issues of IoT devices are increasing with their massive use in healthcare. Recollection of data from devices is not clear to the users so far, and different problems arise including confidentiality, integrity and availability of the information. We analyze security issues mainly related to IoT data storage and transmission in our proposal of healthcare system architecture including cloud services and big data processing of information. We identify protocols needed and security problems including authentication, transmission of data to the cloud, as well as their insufficient anonymization process and the opaque procedure for users in order to control the storage of their data.

Highly Personalized Health Services Using Cloud and Sensors

In a society characterized by aging population and economical crisis it is desirable to reduce the costs of public healthcare systems. It is increasingly necessary to streamline the health system resources leading to the development of new medical services such as telemedicine, monitoring of chronic patients, personalized health services, creating new services for dependants, etc. Those new application and services will significantly increasing the volume of health information to manage, including data from medical and biological sensors, contextual information, health records, reference information, etc., which in turn requires the availability of health applications anywhere, at any time and also access to medical information must be pervasive and mobile. In this paper we propose one potential solution for creating those new services based on cloud computing and vital signs sensors.

A Dictionary Based Protocol over LoRa (Long Range) Technology for Applications in Internet of Things

Internet of the things (IoT) is a new scenario that aims to integrate into the global network “things” or devices such as sensors or embedded electronics equipment, sharing information and enabling interaction with them from anywhere. A very important aspect in IoT applications is the communication protocols used by sensors for sending and exchange information. Traditional protocols used so far do not have the scope and ability to manage a growing up computational elements used in modern IoT applications. New communications schemes based on spread spectrum and Long Range (LoRa) coverage, offer new horizons for design and implement low power and long-range sensor networks. In this paper, we describe a new, robust and lightweight communication protocol implemented over the physical layer of LoRa, providing effectiveness and low power consumption suitable for IoT applications. A coverage analysis in both urban and rural environments confirms the success in the selection of this technology and opens new challenges for developing useful applications in several domains as for example smart cities, smart-health, smart factory, remote monitoring, precision agriculture, energy management and remote monitoring and control.

Improving Health Services Using Cloud Computing, Big Data and Wireless Sensors

In a society characterized by aging population and economical crisis it is desirable to reduce the costs of public healthcare systems. It is increasingly necessary to streamline the health system resources leading to the development of new medical services such as telemedicine, monitoring of chronic patients, personalized health services, creating new services for dependants, etc. Those new application and services will significantly increasing the volume of health information to manage, including data from medical and biological sensors, contextual information, health records, reference information, etc., which in turn requires the availability of health applications anywhere, at any time and also access to medical information must be pervasive and mobile. In this paper we propose one potential solution for creating those new services, especially in outdoors environments, based on cloud computing and vital signs monitoring.