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.

BackgroundDespite the introduction of the Millennium Development Goal to reduce maternal deaths from 400 to 100 per 100,000 live births, the proportion of maternal deaths is still much higher in most developing countries like Ghana. Various interventions have been implemented in Ghana that focus on increasing skilled maternal care. These are especially needed in rural areas. EHealth has the potential to contribute to reducing the challenges in maternal healthcare (MHC) that poor areas suffer. This paper analyzes the potential of eHealth solutions to improve maternal health in rural Ghana as well as the challenges to their implementation. The work was carried out in cooperation with the local health directorate of Kpando Municipality, one of the administrative areas in the Volta Region.MethodsThe study is focused on remote peninsulas and islands in Kpando Municipality. Data was gathered through triangulated research methods. Maternal health challenges were identified using the Three Delays Model for MHC. The three delays are delay in seeking care, delay accessing health facilities, and delay receiving adequate care. Challenges to the implementation of eHealth solutions in remote communities were analyzed using the Drury’s 5C eHealth model for developing countries. The 5Cs correspond to context, community, capacity, connectivity, and content.ResultsThe results show that financial dependence of women, a decision-making process based on previous experiences and traditional beliefs, competitiveness between facilities, organizational loopholes, lack of equipment, and geographical situations directly influence MHC outcomes. EHealth solutions, thanks to the high number of health workers with basic IT skills, have high potential to reduce MHC delays. However, poverty, cultural beliefs, organizational issues, connectivity, and lack of human resources were identified as main challenges to the implementation of eHealth solutions.ConclusionIn Ghana’s rural areas the three delays proposed in the model affect the outcomes of MHC. These delays are influenced by socio-economic status, access to facilities, and quality of care. EHealth solutions show great potential to reduce the delays. Based on the 5C model, a mHealth solution aiming to improve guidance during pregnancy was outlined.

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

Often when performing electrical bioimpedance (EBI) spectroscopy measurements, the obtained EBI data present a hook-like deviation, which is most noticeable at high frequencies in the impedance plane. The deviation is due to a capacitive leakage effect caused by the presence of stray capacitances. In addition to the data deviation being remarkably noticeable at high frequencies in the phase and the reactance spectra, the measured EBI is also altered in the resistance and the modulus. If this EBI data deviation is not properly removed, it interferes with subsequent data analysis processes, especially with Cole model-based analyses. In other words, to perform any accurate analysis of the EBI spectroscopy data, the hook deviation must be properly removed. Td compensation is a method used to compensate the hook deviation present in EBI data; it consists of multiplying the obtained spectrum, Z meas (ω), by a complex exponential in the form of exp(-jωTd). Although the method is well known and accepted, Td compensation cannot entirely correct the hook-like deviation; moreover, it lacks solid scientific grounds. In this work, the Td compensation method is revisited, and it is shown that it should not be used to correct the effect of a capacitive leakage; furthermore, a more developed approach for correcting the hook deviation caused by the capacitive leakage is proposed. The method includes a novel correcting expression and a process for selecting the proper values of expressions that are complex and frequency dependent. The correctness of the novel method is validated with the experimental data obtained from measurements from three different EBI applications. The obtained results confirm the sufficiency and feasibility of the correcting method.

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time. Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5 min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform;(2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student's t test.Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations. Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection. ARTICLE HISTORY

Advances in textile materials, technology and miniaturization of electronics for measurement instrumentation has boosted the development of wearable measurement systems. In several projects sensorized garments and non-invasive instrumentation have been integrated to assess on emotional, cognitive responses as well as physical arousal and status of mental stress through the study of the autonomous nervous system. Assessing the mental state of workers under stressful conditions is critical to identify which workers are in the proper state of mind and which are not ready to undertake a mission, which might consequently risk their own life and the lives of others. The project Assessment in Real Time of the Stress in Combatants (ATREC) aims to enable real time assessment of mental stress of the Spanish Armed Forces during military activities using a wearable measurement system containing sensorized garments and textile-enabled non-invasive instrumentation. This work describes the multiparametric sensorized garments and measurement instrumentation implemented in the first phase of the project required to evaluate physiological indicators and recording candidates that can be useful for detection of mental stress. For such purpose different sensorized garments have been constructed: a OPEN ACCESSSensors 2013, 13 8998 textrode chest-strap system with six repositionable textrodes, a sensorized glove and an upper-arm strap. The implemented textile-enabled instrumentation contains one skin galvanometer, two temperature sensors for skin and environmental temperature and an impedance pneumographer containing a 1-channel ECG amplifier to record cardiogenic biopotentials. With such combinations of garments and non-invasive measurement devices, a multiparametric wearable measurement system has been implemented able to record the following physiological parameters: heart and respiration rate, skin galvanic response, environmental and peripheral temperature. To ensure the proper functioning of the implemented garments and devices the full series of 12 sets have been functionally tested recording cardiogenic biopotential, thoracic impedance, galvanic skin response and temperature values. The experimental results indicate that the implemented wearable measurement systems operate according to the specifications and are ready to be used for mental stress experiments, which will be executed in the coming phases of the project with dozens of healthy volunteers.

Determination of body fluids is a useful common practice in determination of disease mechanisms and treatments. Bioimpedance spectroscopy (BIS) methods are non-invasive, inexpensive and rapid alternatives to reference methods such as tracer dilution. However, they are indirect and their robustness and validity are unclear. In this article, state of the art methods are reviewed, their drawbacks identified and new methods are proposed. All methods were tested on a clinical database of patients receiving growth hormone replacement therapy. Results indicated that most BIS methods are similarly accurate (e.g. < 0.5 ±   3.0% mean percentage difference for total body water) for estimation of body fluids. A new model for calculation is proposed that performs equally well for all fluid compartments (total body water, extra- and intracellular water). It is suggested that the main source of error in extracellular water estimation is due to anisotropy, in total body water estimation to the uncertainty associated with intracellular resistivity and in determination of intracellular water a combination of both.

Activities around applications of Electrical Bioimpedance Spectroscopy (EBIS) have proliferated in the past decade significantly. Most of these activities have been focused in the analysis of the EBIS measurements, which eventually might enable novel applications. In Body Composition Assessment (BCA), the most common analysis approach currently used in EBIS is based on the Cole function, which most often requires curve fitting. One of the most implemented approaches for obtaining the Cole parameters is performed in the impedance plane through the geometrical properties that the Cole function exhibit in such domain as depressed semi-circle. To fit the measured impedance data to a semi-circle in the impedance plane, obtaining the Cole parameters in an indirect and sequential manner has several drawbacks. Applying a Non-Linear Least Square (NLLS) iterative fitting on the spectroscopy measurement, obtains the Cole parameters considering the frequency information contained in the measurement. In this work, from experimental total right side EBIS measurements, the BCA parameters have been obtained to assess the amount and distribution of whole body fluids. The values for the BCA parameters have been obtained using values for the Cole parameters estimated with both approaches: circular fitting on the impedance plane and NLLS impedance-only fitting. The comparison of the values obtained for the BCA parameters with both methods confirms that the NLLS impedance-only is an effective alternative as Cole parameter estimation method in BCA from EBIS measurements. Using the modulus of the Cole function as the model for the fitting would eliminate the need for performing phase detection in the acquisition process, simplifying the hardware specifications of the measurement instrumentation when implementing a bioimpedance spectrometer.