A portable, Internet-based EEG/Auditory Evoked Potential (AEP) monitoring system was developed for remote electrophysiological studies during sleep. The system records EEG/AEP simultaneously at the subject’s home for increased comfort and flexibility. The system provides simultaneous recording and remote viewing of EEG, EMG and EOG waves and allows on-line averaging of auditory evoked potentials. The design allows the recording of all major AEP components (brainstem, middle and late latency EPs) and constituent single sweep EEG epochs. Auditory stimulation is remotely controlled from any internet-connected PC. The developed platform consists of a portable server computer for data acquisition and secured data transmission to the Internet, a web server for temporary storage, and a remote viewing station. During operation, signals are acquired during sleep and transmitted to the secured web server for controlled access viewing. The remote viewer station allows the user to continuously visualize the auditory evoked potentials, modify auditory stimuli at any time and adjust system parameters for its online computation. The developed internet-based EEG/EP system has been tested in a laboratory environment. Preliminary results demonstrate feasibility of remote real-time acquisition and viewing of EEG and EPs and future potential for home monitoring and telemedicine applications.

Developing a Web-based Fuzzy Inference Tool for cardiovascular risk assessment. The tool uses evidence-based medicine inference rules for membership classification. Methods. The system framework allows adding variables such as gender, age, weight, height, medication intake, and blood pressure, with various types of membership functions based on classification rules. Results. By inputting patient clinical data, the tool allows health professionals to obtain a prediction of cardiovascular risk. The tool can also be later used to predict other types of risks including cognitive and physical disease conditions.

Objetivo. Desarrollar una h erramienta Fuzzy de Inferencia basada en Web para la evaluación del riesgo cardiovascular. La herramienta hace uso de reglas de inferencia de medicina basada en evidencia para la clasificación de membresía. Métodos. El marco del sistema permite la adición de variables como el género, la edad, el peso, la altura, la ingesta de medicamentos, y la tensión arterial, con varios tipos de funciones de pertenencia basada en reglas de clasificación. Resultados. La herramienta permite a los profesionales de la salud ingresar los datos clínicos del paciente y obtener una predicción del riesgo cardiovascular. La herramienta también puede ser utilizada más adelante para predecir otros tipos de riesgos, incluyendo condiciones de la enfermedad cognitivas y físicas.

Objetivo: Desarrollo de un atlas Web para el intercambio colaborativo, procesamiento y análisis de imágenes diagnósticas. Materiales y métodos: Uso de herramientas Web 2.0 para desarrollo de Ambientes de Aprendizaje Personalizado para el aprendizaje social y la construcción e intercambio del conocimiento. Resultados: La plataforma permite subir, visualizar, procesar y comentar las imágenes médicas de forma colaborativa. El sistema posee un módulo de red social, módulo de Webinars para análisis de casos en tiempo real, y módulo de visualización, anotación, análisis y procesamiento de imágenes. El sistema tiene usos como un gran repositorio de imágenes diagnósticas creado y validado por la comunidad médica y utilizado para la formación e investigación, así como para la referencia y segunda opinión de casos.

Development of a Web-based atlas for collaborative image sharing, processing and analysis of diagnostic images. Materials and methods: Use of Web 2.0 Personalized Learning Environment tools for social learning and knowledge construction and sharing. Results: The platform allows registered users to upload, visualize, process and comment medical images in a collaborative manner. The system contains a social network module for open case discussion, a video conference and webinar module for real time case analysis, and an image visualization, annotation and processing module for image analysis. The developed open-access platform serves as a large community-created and validated free-repository of diagnostic medical images to be used for training, research as well as reference and second opinion of cases.