Home-Automation System

Nuestro proyecto trata de obtener un sistema centralizado para el manejo y monitorización de un conjunto de aparatos eléctricos del hogar, tales como luces, cámaras, sensores, y otros aparatos mediante una aplicación para dispositivos móviles Android. También se facilita una herramienta web para administrar dichos aparatos. Nuestro sistema da soporte al manejo individual y manual de estos aparatos, por ejemplo encender una lámpara, así como la posibilidad de incluir programas que se ejecuten a una determinada hora, y con una determinada recurrencia. Por ejemplo, se puede programar el encendido de una luz todos los días a las 20:00. Además, también se pueden crear reglas que, dado una determinada situación, realicen una serie de acciones. Por ejemplo, si se detecta que la luminosidad baja de cierto valor (detectado mediante un sensor de luz), se encienda una lámpara. Para conseguir esto se ha realizado una aplicación centralizada, a modo de servidor, que se comunica con los aparatos eléctricos mediante diferentes protocolos de comunicación, así como con el dispositivo móvil Android, y una aplicación web administrativa, a través de un portal de servicios web.

Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

Background: Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods: This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results: In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better. Conclusions: Five clinical predictors easily available in the ED, and also in the primary care setting, can be used to create a simple and easily obtained score that allows clinicians to stratify patients with eCOPD upon ED arrival and guide the medical decision-making process.