Diego Gachet

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.

Identification technologies to support Alzheimer contexts

Alzheimers disease makes great demands on care by assistants, due to the fact that they cannot distract their attention from patients while they are at the same time managing records. For that reason, technologies to complement this process need to be adapted. In this work we present a proposal to adapt identification technologies: Radiofrequency Identification (RFID) and Near Field Communications (NFC), focusing especially on the last one. We fuse both technologies and apply them to an Alzheimers day center. Patients are tagged with two kinds of labels: 13.56Mhz.Mifare for NFC and UHF for RFID. With the first one we tag the context, which means patients, devices (displays, exercise books, etc) and places. With a simple interaction, which involves touching tags with mobile phones, it is possible to manage the information easily. Moreover, with RFID, we localize each patient by the simple act of their passing by an antenna placed in the doors.

The SINAMED and ISIS projects: applying text mining techniques to improve access to a medical digital library

Intelligent information access systems integrate text mining and content analysis capabilities as a relevant element in an increasing way. In this paper we present our work focused on the integration of text categorization and summarization to improve information access on a specific medical domain, patient clinical records and related scientific documentation, in the framework of two different research projects: SINAMED and ISIS, developed by a consortium of two research groups from two universities, one hospital and one software development firm. SINAMED has a basic research orientation and its goal is to design new text categorization and summarization algorithms based on the utilization of lexical resources in the biomedical domain. ISIS is a R&D project with a more applied and technology-transfer orientation, focused on more direct practical aspects of the utilization in a concrete public health institution.

Distributed Big Data Techniques for Health Sensor Information Processing

Recent advances in wireless sensors technology applied to e-health allow the development of “personal medicine” concept, whose main goal is to identify specific therapies that make safe and effective individualized treatment of patients based, for example, in health status remote monitoring. Also the existence of multiple sensor devices in Hospital Units like ICUs (Intensive Care Units) constitute a big source of data, increasing the volume of health information to be analyzed in order to detect or predict abnormal situations in patients. In order to process this huge volume of information it is necessary to use Big Data and IoT technologies. In this paper, we present a general approach for sensor’s information processing and analysis based on Big Data concepts and to describe the use of common tools and techniques for storing, filtering and processing data coming from sensors in an ICU using a distributed architecture based on cloud computing. The proposed system has been developed around Big Data paradigms using bio-signals sensors information and machine learning algorithms for prediction of outcomes.

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.

Big Data Processing of Bio-signal Sensors Information for Self-Management of Health and Diseases

These last years developed countries and specially European countries are characterized by aging population and economical crisis, as a consequence, the funds dedicated to social services has been diminished specially those dedicated to healthcare, is then desirable to optimize the costs of public and private healthcare systems reducing the affluence of chronic and dependant people to care centers and enabling the management of chronic diseases outside institutions. It is necessary to streamline the health system resources leading to the development of new medical services based on telemedicine and biomedical sensors. New health applications based on remote monitoring will significantly increasing the volume of health information to store, manage and analyze, including heterogeneous data coming from medical records and biomedical sensors. The Big Data and IoT concepts and techniques offer an integrated approach to develop a suitable architecture for an adequate treatment of this kind of information.

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.

A Robust and Lightweight Protocol Over Long Range (LoRa) Technology for Applications in Smart Cities

The implementation of Smart Cities requires technologies such as the Internet of Things (IoT). This paradigm aims to integrate and use in Internet electronic embedded devices like sensors, in order to share information and allowing interaction from anywhere. Standard communication protocols used in IoT for data transmission are based in general on FSK (Frequency Shift Keying) techniques that do not have the range and necessary performance to deal with this new scenery. With this situation in mind Semtech Technologies have developed a new modulation technique called LoRa (Long Range) based on spread spectrum that offer a new communication model for low power and long range networks, impossible to implement with other techniques. In this paper, we describe a new communication protocol implemented over the physical layer of LoRa providing effectiveness, robustness and low power consumption suitable for IoT applications in the context of smart cities. Results obtained related with the coverage analysis confirm the success of the selection of this technology and opens new horizons for developing useful applications in domains like smart cities, e-health, smart factory, remote monitoring and control, etc.

Helping Elderly People and Persons with Disability to Access the Information Society

NAVIGA is an European project whose main goal is to design and develop a technological platform allowing elderly people and persons with disability to access the Internet and the Information Society through an innovative and adaptable navigator. NAVIGA also allows the creation of services targeted to social networks, mind training and personalized health care.

Risk Patient Help and Location System Using Mobile Technologies

This paper explores the feasibility of the inclusion of information and communications technologies for helping and localizing risk and early discharge patients, and suggests innovative actions in the area of E- Health services. The system will be applied to patients with cardiovascular or Chronic Obstructive Pulmonarry Diseases (COPD) as well as to ambulatory surgery patients. The proposed system will allow to transmit the patient’s location and some information about their illness to the Hospital or care centre.