The overall aim of our research is to develop a monitoring system for neonatal intensive care units. Long-term EEG monitoring in newborns require that the electrodes don’t harm the sensitive skin of the baby, an especially relevant feature for premature babies. Our approach to EEG monitoring is based on several electrodes distributed over the head of the baby, and since the weight of the head always will be on some of them, any type of hard electrode will inevitably cause a pressure-point that can irritate the skin. Therefore, we propose the use of soft conductive textiles as EEG electrodes, primarily for neonates, but also for other kinds of unobtrusive long-term monitoring. In this paper we have tested two types of textile electrodes on five healthy adults and compared them to standard high quality electrodes. The acquired signals were compared with respect to morphology, frequency distribution, spectral coherence, correlation and power line interference sensitivity, and the signals were found to be similar in most respects. The good measurement performance exhibited by the textile electrodes indicates that they are feasible candidates for EEG recording, opening the door for long-term EEG monitoring applications.

The Spanish Ministry of Defense, through its Future Combatant program, has sought to develop technology aids with the aim of extending combatants' operational capabilities. Within this framework the ATREC project funded by the “Coincidente” program aims at analyzing diverse biometrics to assess by real time monitoring the stress levels of combatants. This project combines multidisciplinary disciplines and fields, including wearable instrumentation, textile technology, signal processing, pattern recognition and psychological analysis of the obtained information. In this work the ATREC project is described, including the different execution phases, the wearable biomedical measurement systems, the experimental setup, the biomedical signal analysis and speech processing performed. The preliminary results obtained from the data analysis collected during the first phase of the project are presented, indicating the good classification performance exhibited when using features obtained from electrocardiographic recordings and electrical bioimpedance measurements from the thorax. These results suggest that cardiac and respiration activity offer better biomarkers for assessment of stress than speech, galvanic skin response or skin temperature when recorded with wearable biomedical measurement systems.

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Healthcare organizations are confronted with challenges including the contention between tightening budgets and increased care needs. In the light of these challenges, they are becoming increasingly aware of the need to improve their processes to ensure quality of care for patients. To identify process improvement opportunities, a thorough process analysis is required, which can be based on real-life process execution data captured by health information systems. Process mining is a research field that focuses on the development of techniques to extract process-related insights from process execution data, providing valuable and previously unknown information to instigate evidence-based process improvement in healthcare. However, despite the potential of process mining, its uptake in healthcare organizations outside case studies in a research context is rather limited. This observation was the starting point for an international brainstorm seminar. Based on the seminar's outcomes and with the ambition to stimulate a more widespread use of process mining in healthcare, this paper formulates recommendations to enhance the usability and understandability of process mining in healthcare. These recommendations are mainly targeted towards process mining researchers and the community to consider when developing a new research agenda for process mining in healthcare. Moreover, a limited number of recommendations are directed towards healthcare organizations and health information systems vendors, when shaping an environment to enable the continuous use of process mining.

Impedance Cardiography (ICG) is a non-invasive method for monitoring cardiac dynamics using Electrical Bioimpedance (EBI) measurements. Since its appearance more than 40 years ago, ICG has been used for assessing hemodynamic parameters. This paper present a measurement system based on two System on Chip (SoC) solutions and Raspberry PI, implementing both a full 3-lead ECG recorder and an impedance cardiographer, for educational and research development purposes. Raspberry PI is a platform supporting Do-It-Yourself project and education applications across the world. The development is part of Biosignal PI, an open hardware platform focusing in quick prototyping of physiological measurement instrumentation. The SoC used for sensing cardiac biopotential is the ADAS1000, and for the EBI measurement is the AD5933. The recording were wirelessly transmitted through Bluetooth to a PC, where the waveforms were displayed, and hemodynamic parameters such as heart rate, stroke volume, ejection time and cardiac output were extracted from the ICG and ECG recordings. These results show how Raspberry PI can be used for quick prototyping using relatively widely available and affordable components, for supporting developers in research and engineering education. The design and development documents, will be available on www.BiosignalPI.com, for open access under a Non Commercial-Share A like 4.0 International License.

Hypoxia/ischaemia is the most common cause of brain damage in neonates. Thousands of newborn children suffer from perinatal asphyxia every year. The cells go through a response mechanism during hypoxia/ischaemia, to maintain the cellular viability and, as a response to the hypoxic/ischaemic insult, the composition and the structure of the cellular environment are altered. The alterations in the ionic concentration of the intra-and extracellular and the consequent cytotoxic oedema, cell swelling, modify the electrical properties of the constituted tissue. The changes produced can be easily measured using electrical impedance instrumentation. In this paper, we report the results from an impedance spectroscopy study on the effects of the hypoxia on the perinatal brain. The transencephalic impedance, both resistance and reactance, was measured in newborn piglets using the four-electrode method in the frequency range from 20 kHz to 750 kHz and the experimental results were compared with numerical results from a simulation of a suspension of cells during cell swelling. The experimental results make clear the frequency dependence of the bioelectrical impedance, confirm that the variation of resistance is more sensitive at low than at high frequencies and show that the reactance changes substantially during hypoxia. The resemblance between the experimental and numerical results proves the validity of modelling tissue as a suspension of cells and confirms the importance of the cellular oedema process in the alterations of the electrical properties of biological tissue. The study of the effects of hypoxia/ischaemia in the bioelectrical properties of tissue may lead to the development of useful clinical tools based on the application of bioelectrical impedance technology.

The increasing number of applications of electrical bioimpedance measurements in biomedical practice, together with continuous advances in textile technology, has encouraged several researchers to make the first attempts to develop portable, even wearable, electrical bioimpedance measurement systems. The main target of these systems is personal and home monitoring. Analog Devices has made available AD5933, a new system-onchip fully integrated electrical impedance spectrometer, which might allow the implementation of minimum-size instrumentation for electrical bioimpedance measurements. However, AD5933 as such is not suitable for most applications of electrical bioimpedance. In this work, we present a relatively simple analog front-end that adapts AD5933 to a four-electrode strategy, allowing its use in biomedical applications for the first time. The resulting impedance measurements exhibit a very good performance in aspects like load dynamic range and accuracy. This type of minimum-size, system-on-chip-based bioimpedance measurement system would lead researchers to develop and implement light and wearable electrical bioimpedance systems for home and personal health monitoring applications, a new and huge niche for medical technology development.

Very often in Electrical Bioimpedance (EBI) spectroscopy measurements the presence of stray capacitances creates a measurement artefact commonly known as Hook Effect . Such an artefact creates a hook-alike deviation of the EBI data noticeable when representing the measurement on the impedance plane. Such Hook Effect is noticeable at high frequencies but it also causes a data deviation at lower measurement frequencies. In order to perform any accurate analysis of the EBI spectroscopy data, the influence of the Hook Effect must be removed. An established method to compensate the hook effect is the well known Td compensation , which consists on multiplying the obtained spectrum, Z meas (ω) by a complex exponential in the form of exp[jωTd]. Such a method cannot correct entirely the Hook Effect since the hook-alike deviation occurs a broad frequency range in both magnitude and phase of the measured impedance, and by using a scalar value for Td . First a scalar only modifies the phase of the measured impedance and second, a single value can truly corrects the Hook Effect only at a single frequency. In addition, the process to select a value for the scalar Td by an iterative process with the aim to obtain the best Cole fitting lacks solid scientific grounds. In this work the Td compensation method is revisited and a modified approach for correcting the Hook Effect including a novel method for selecting the correcting values is proposed. The initial validation results confirm that the proposed method entirely corrects the Hook Effect at all frequencies.

QC 20120206