M. Elena

Fast Technique for Noninvasive Fetal ECG Extraction

This letter describes a fast and very simple algorithm for estimating the fetal electrocardiogram (FECG). It is based on independent component analysis, but we substitute its computationally demanding calculations for a much simpler procedure. The resulting method consists of two steps: 1) a dimensionality reduction step and 2) a computationally light postprocessing stage used to enhance the FECG signal.

The Maternal Abdominal ECG as Input to MICA in the Fetal ECG Extraction Problem

This letter presents a successful system for recovering the fetal electrocardiogram using multidimensional ICA (MICA). MICA requires as many observations as sources. To increase the number of observations, MICA is often applied to data sets that include measurements taken at the mothers thoracic region. However, experiments suggest that the propagation from the maternal heart to the mothers abdomen is not a simple delay, and that approach may fail. Alternatively, our method first estimates the maternal ECG directly from the mothers abdomen. Then, inputs this estimated ECG to MICA. Experiments show superior performance as compared with the traditional approach.

Design of a mobile telecardiology system using GPRS/GSM technology

This paper presents the design and development of a portable electrocardiograph to allow the on-line remote monitoring and real-time cardiac diseases diagnostics of patients from the specialist. This prototype has been satisfactory implemented finding a good balance between optimal signal processing and power consumption using a GPRS/GSM modem and a SMT low voltage microprocessor board.

Monte Carlo method for the evaluation of symptom association.

Gastroesophageal monitoring is limited to 96 hours by the current technology. This work presents a computational model to investigate symptom association in gastroesophageal reflux disease with larger data samples proving important deficiencies of the current methodology that must be taking into account in clinical evaluation. A computational model based on Monte Carlo analysis was implemented to simulate patients with known statistical characteristics Thus, sets of 2000 10-day-long recordings were simulated and analyzed using the symptom index (SI), the symptom sensitivity index (SSI), and the symptom association probability (SAP). Afterwards, linear regression was applied to define the dependency of these indexes with the number of reflux, the number of symptoms, the duration of the monitoring, and the probability of association. All the indexes were biased estimators of symptom association and therefore they do not consider the effect of chance: when symptom and reflux were completely uncorrelated, the values of the indexes under study were greater than zero. On the other hand, longer recording reduced variability in the estimation of the SI and the SSI while increasing the value of the SAP. Furthermore, if the number of symptoms remains below one-tenth of the number of reflux episodes, it is not possible to achieve a positive value of the SSI. A limitation of this computational model is that it does not consider feeding and sleeping periods, differences between reflux episodes or causation. However, the conclusions are not affected by these limitations. These facts represent important limitations in symptom association analysis, and therefore, invasive treatments must not be considered based on the value of these indexes only until a new methodology provides a more reliable assessment.

The binomial symptom index: toward an optimal method for the evaluation of symptom association in gastroesophageal reflux

The evaluation of symptom association in gastroesophageal reflux is an open problem. The scientific literature reports important deficiencies and clinicians are claiming a new methodology. This article provides an optimal method for the evaluation of symptom association, the binomial symptom index (BSI).

CARDIOSMART: intelligent cardiology monitoring system using GPS/GPRS networks

Cardiosmart project is based on a portable terminal for the acquisition, pre-processing and transmission of cardiac signals and the GPRS network (PAC) used to send the ECG signal to a host computer in the medical services provider centre or a specialist consulting room. The PAC terminal includes a GPRS modem for data transmission, a GPS device to provide an accurate location of the patient, and an intelligent heart pathology detection system. The objective of this project consists of the development of a European Cardiology On-line Monitoring System using GPRS/GSM wireless communication technology. The utilisation of electrocardiogram transmission will improve efficiency of medical care and service for patients if they could be monitored constantly by health care providers. A direct and almost instant medical support is provided, specially to those patients that vanish during a heart attack.

Design of a Remote Monitoring Platform for Telemedicine Systems Using New Generation Mobile Services

A new global Telemedicine platform is presented, using emergent mobile technologies. The system has been designed to support, not only remote biological signal monitoring, but value-added services for diagnosis and medical care, too, both of them working in real time. The system is based on a hierarchical medical database, designed to contain a huge quantity of useful clinical information. The access and configuration of the platform is carried out using a web interface, specially designed to manage the functionality of the system proposed. Communication between different mobiles and the communication centre is supported on new technologies offered by Minerva Project, while low range link is based on novelty wireless standards to connect sensors and mobile devices.

Inter-reflux and bolus clearance times in non-pathologic pediatric patients: data support computational models.

Previous contributions suggested that gastroesophageal reflux can be modeled in terms of a Poisson process. This study aims to provide empirical data to validate this statement in pediatric patients so that computational models can be broadly used as an alternative for research. A retrospective review of 63 pediatric patients who underwent 24-hour impedance-pH monitoring to discard gastroesophageal reflux disease was conducted in this study. Patients were grouped by age as preterm (21), infants (21), and children (21). All the tracings were analyzed by a trained physician who identified the reflux entry and the bolus clearance time of each episode. The time between reflux episodes was tested against three probability distributions (gamma, exponential and inverse Gaussian) whereas the bolus clearance time was tested against a normal probability distribution. Parameters were estimated using the maximum likelihood method. The Kolmogorov-Smirnov test and the Kullback-Leibler divergence were computed to evaluate the goodness of fit. One-way analysis of variance was applied to compare results along the three groups. Exponential fitting for inter-reflux time was successful in 90.48% of children older than 1 year. The overall reflux rate was 57.58 reflux episodes per day whereas the mean bolus clearance time ranged between 10.87 in preterm subjects and 12.05 in children, showing a good Gaussian fitting. The time between reflux episodes can be modeled in terms of a Poisson process in non tube-fed patients, whereas the bolus clearance time follows a normal distribution in all cases.

IVITooL. A scalable platform for medical data integration

In this paper, we present IVITooL (IntelliVue® Interface Tool), a valuable self-designed application software for the integration of medical information from different Intensive Care Units devices. Nowadays, most hospitals, including Intensive Care Areas are equipped with many cutting-edge devices for diagnosis, such as patient monitors. These devices provide huge volumes of data which should be analyzed later. The fact that each device uses a different standard for data transmission and storage greatly hinders the process of diagnosis. To solve this problem, the design of a software platform capable of interacting with a range of Philips® monitors is presented. In addition to be a high valuable interface, it also allows the inclusion of information from any other device, hence allowing the graphical representation and storage of different signals from different devices, resulting in an enormous benefit to early diagnosis of diseases.

Smart Sensors for Environmental BioSecurity Control at Operating Rooms

At hospitals, as well of the purely clinical needs, special attention should be paid to hygiene. The sterilization and cleanliness of the instruments is a superseded topic; however, the control of particles and contaminant elements in the air is not so obvious. The hospital air conditioning systems should not contribute to the production, amplification and/or distribution of pollutants, so it is important to have a regular maintenance and operation of them and monitor their hygienic conditions. The objective of this paper is to review the present situation on controlled environmental rooms at hospital (especially in operating rooms), so as to identify and propose a new way of actuation. In particular, we propose the usage of smart biosensors to fulfill the environmental needs and to ensure the correct operation of these rooms.