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The reduced Heart Rate Variability (HRV) is believed to be associated with several diseases such as congestive heart failure, diabetes and chronic kidney diseases (CKD). In these cases, HRV biofeedback may be a potential intervention method to increase HRV which in turn is beneficial to these patients. In this work, a real-time Android biofeedback application based on a Bluetooth enabled ECG and thoracic...
Personalised Health Systems (PHS) that could benefit the life quality of the patients as well as decreasing the health care costs for society among other factors are arisen. The purpose of this paper is to study the capabilities of the System-on-Chip Impedance Network Analyser AD5933 performing high speed single frequency continuous bioimpedance measurements. From a theoretical analysis, the minimum...
One of the most common measurement artifacts present in Electrical Bioimpedance Spectroscopy measurements (EBIS) comes from the capacitive leakage effect resulting from parasitic stray capacitances. This artifact produces a deviation in the measured impedance spectrum that is most noticeable at higher frequencies. The artifact taints the spectroscopy measurement increasing the difficulty of producing...
This paper presents a novel frequency distribution scheme intended to provide more accurate estimations of Cole parameters. Nowadays a logarithmic frequency distribution is mostly used in Electrical Bioimpedance Spectroscopy (EBIS) applications. However it is not optimized following any criterion. Our hypothesis is that an EBIS signal contains more information where the variation of the measurement...
Electrical Bioimpedance Spectroscopy (EBIS) is currently used in different tissue characterization applications. In this work we aim to use EBIS to study changes in electrical properties of the cerebral tissues after an incident of hemorrhage/ischemic stroke. To do so a case-control study was conducted using six controls and three stroke cases. The preliminary results of this study show that by using...
Aim: To evaluate the prognostic capacity of a new method for automatic quantification of the length of suppression time in the electroencephalogram (EEG) of a group of asphyxiated newborn infants.
Methods: Twenty‐one full‐term newborn infants who had been resuscitated for severe birth asphyxia were studied. Eight channel continuous EEG was recorded for prolonged time periods during the first days...
Advances on System-On-Chip and Textile technology allows the development of Textile-enabled measurement instrumentation. Textile Electrodes (Textrodes) have been proven reliable for performing Electrical Bioimpedance Spectroscopy (EBIS) measurements, and the availability of a integrated circuit impedance spectrometer, the AD5933, has allowed the implementation of small size EBIS spectrometers. In...
Electrical Bioimpedance Spectroscopy (EBIS) has been widely used for assessment of total body composition and fluid distribution. (EBIS) measurements are commonly performed with electrolytic electrodes placed on the wrist and the ankle with a rather small skin-electrode contact area. The use of textile garments for EBI requires the integration of textrodes with a larger contact area surrounding the...
Objective: To study whether indomethacin used in conventional dose for closure of patent ductus arteriosus affects cerebral function measured by Electroencephalograms (EEG) evaluated by quantitative measures.
Study design: Seven premature neonates with haemodynamically significant persistent ductus arteriosus were recruited. EEG were recorded before, during and after an intravenous infusion of 0...
Electrical Bioimpedance (EBI) is one of the non-invasive monitoring technologies that could benefit from the emerging textile based measurement systems. If reliable and reproducible EBI measurements could be done with textile electrodes, that would facilitate the utilization of EBI-based personalized healthcare monitoring applications. In this work the performance of a custom-made dry-textile electrode...
Work has been intensified around the integration of textile and measurement technology for physiological measurements in the last years. As a result nowadays it is possible to find available commercial products for cardiovascular personal healthcare monitoring. Most of the efforts have been focused in the acquisition of EKG for cardiovascular monitoring where textile electrodes have shown satisfactory...
Home e-health systems and services are revealed as one of the most important challenges to promote quality of life related to health in the information society. Leading companies have worked on e-health systems although the majority of them are addressed to hospital or primary care settings. The solution detailed in this paper offers a personal health system to be integrated with smart home services...
Hidden Markov Models (HMM) and Support Vector Machines (SVM) using unsupervised and supervised training, respectively, were compared with respect to their ability to correctly classify burst and suppression in neonatal EEG. Each classifier was fed five feature signals extracted from EEG signals from six full term infants who had suffered from perinatal asphyxia. Visual inspection of the EEG by an...
In order to improve the care of Chronic Heart Failure (CHF) patients, a system has been developed for monitoring symptoms and document subjective judgments on health conditions in a home environment. Since system usability is an important issue, a two step evaluation of the solution was conducted. First a ten-patient survey was conducted, which was aimed at spotting possible problem areas. The second...
Fisher's linear discriminant, a feed-forward neural network (NN) and a support vector machine (SVM) are compared with respect to their ability to distinguish bursts from suppression in burst-suppression electroencephalogram (EEG) signals using five features inherent in the EEG as input. The study is based on EEG signals from six full term infants who have suffered from perinatal asphyxia, and the...
A Support Vector Machine (SVM) was trained to distinguish bursts from suppression in burst-suppression EEG, using five features inherent in the electro-encephalogram (EEG) as input. The study was based on data from six full term infants who had suffered from perinatal asphyxia, and the machine was trained with reference classifications made by an experienced electroencephalographer. The results show...
There have been several studies of the application of electrical bioimpedance technology for brain monitoring in the past years. They have targeted a variety of events and injuries e.g. epilepsy or stroke. The current density distribution and the voltage lead field associated with an impedance measurement setup is of critical importance for the proper analysis of any dynamics in the impedance measurement...
Eight features inherent in the electro-encephalogram (EEG) have been extracted and evaluated with respect to their ability to distinguish bursts from suppression in burst-suppression EEG. The study is based on EEG from six full term infants who had suffered from lack of oxygen during birth. The features were used as input in a neural network, which was trained on reference data segmented by an experienced...
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