Jesús Lázaro

Pulse Rate Variability Analysis for Discrimination of Sleep-Apnea-Related Decreases in the Amplitude Fluctuations of Pulse Photoplethysmographic Signal in Children

A technique for ambulatory diagnosis of the obstructive sleep apnea syndrome (OSAS) in children based on pulse photoplethysmographic (PPG) signal is presented. Decreases in amplitude fluctuations of the PPG signal (DAP) events have been proposed as OSAS discriminator, since they are related to vasoconstriction associated to apnea. Heart rate variability (HRV) analysis during these DAP events has been proposed to discriminate between DAP events related or unrelated to an apneic event. The use of HRV requires electrocardiogram (ECG) as an additional recording, meaning a disadvantage that takes more relevance in sleep studies context where the number of sensors is tried to be minimized in order not to affect the physiological sleep. This study proposes the use of pulse rate variability (PRV) extracted from the PPG signal instead of HRV. Polysomnographic registers from 21 children (aged 4.47 ±2.04 years) were studied. The subject classification based on DAP events and PRV analysis obtained an accuracy of 86.67% which represents an improvement of 6.67% with respect to the HRV analysis. These results suggest that PRV can be used in apnea detectors based on DAP events, to discriminate apneic from nonapneic events avoiding the need for ECG recordings.

A quantitative approach to the classification of hypospermatogenesis in testicular biopsies for infertility

Absolute counts of germ cells were performed in 110 testicular biopsy specimens from 59 patients with either idiopathic infertility or varicocele and in a series of five autopsy specimens from age-matched controls. The tubular diameter, thickness of the tubular wall, and density of Leydig cells were measured. The following patterns were identified by germ-cell counts in the biopsy specimens: normal cell population, mild decrease in germ cells with normal ratio of cell types, advanced hypospermatogenesis with abnormal ratio of cell types, and Sertoli cell only. This sequence of progressive hypospermatogenesis was remarkably similar in both series. A separate category of maturation arrest was not recognized. Cell counts also correlated between right- and left-sided samples from the same patient in both series of biopsies. Reduction of tubular diameter, thickening of the tubular wall, and increase in Leydig cell density were often seen in severe stages of germ-cell impairment, although with an irregular distribution.

Inclusion of Respiratory Frequency Information in Heart Rate Variability Analysis for Stress Assessment

Respiratory rate and heart rate variability (HRV) are studied as stress markers in a database of young healthy volunteers subjected to acute emotional stress, induced by a modification of the Trier Social Stress Test. First, instantaneous frequency domain HRV parameters are computed using time-frequency analysis in the classical bands. Then, the respiratory rate is estimated and this information is included in HRV analysis in two ways: 1) redefining the high-frequency (HF) band to be centered at respiratory frequency; 2) excluding from the analysis those instants where respiratory frequency falls within the low-frequency (LF) band. Classical frequency domain HRV indices scarcely show statistical differences during stress. However, when including respiratory frequency information in HRV analysis, the normalized LF power as well as the LF/HF ratio significantly increase during stress (p-value <; 0.05 according to the Wilcoxon test), revealing higher sympathetic dominance. The LF power increases during stress, only being significantly different in a stress anticipation stage, while the HF power decreases during stress, only being significantly different during the stress task demanding attention. Our results support that joint analysis of respiration and HRV obtains a more reliable characterization of autonomic nervous response to stress. In addition, the respiratory rate is observed to be higher and less stable during stress than during relax (p-value <; 0.05 according to the Wilcoxon test) being the most discriminative index for stress stratification (AUC = 88.2%).

3D-geological structures with digital elevation models using GPU programming

We present an application that visualises three-dimensional geological structures with digital terrain models. The three-dimensional structures are displayed as their intersections with two-dimensional surfaces that may be defined analytically (e.g., sections) or with grid meshes in the case of irregular surfaces such as the digital terrain models. The process begins with classic techniques of terrain visualisation using hypsometric shading with textures. Then, geometric transformations that are easily conceived and programmed are added, thus representing the three-dimensional structures with their location and orientation. Functions of three variables are used to define the geological structures, and data from digital terrain models are used as one of the variables. This provides a simple source code and results in a short calculation time. Additionally, the process of generating new textures can be performed by a Graphics Processing Unit (GPU), thereby making real-time processing very effective and providing the possibility of displaying the simulation of geological structures in motion. Display Omitted Visualisation of 3D geological structures with DEMs can be done in real-time with GPUs.Models of geological structures can be built using three-dimensional functions.3D functions allow changes in models and help the interpretation of the geology in the real world.3D functions allow the combination of structural domains and overlapping of folding phases.

Electrocardiogram derived respiration from QRS slopes: Evaluation with stress testing recordings

A method for respiratory rate estimation from electrocardiogram (ECG), based on variations in QRS complexes slopes, is evaluated over stress testing recordings. Besides the 12 standard, and the 3 vectorcardiogram (VCG), 2 additional leads derived from the VCG are analyzed. A total of 34 slope series were studied, 2 for each lead: slopes between the peaks of the Q and R waves, and between the peaks of the R and S waves. Respiratory rate is estimated by using a time-frequency based algorithm which can combine information from several derived respiration signals. Evaluation was performed over a database containing ECG and respiratory signals simultaneously recorded from 30 subjects spontaneously breathing during a stress test. Respiratory rate estimation is performed with information of 4 different combinations of QRS slope series. The best results in respiratory rate estimation error terms are -1.07 ± 8.86% (-11.47 ± 37.97 mHz). These results suggest that proposed methods based on QRS slopes are highly suitable for respiratory rate estimation from ECG signal, specially at very non-stationary and noise scenarios as stress test.

Sensitivity analysis of main variables present in flash flood processes. Application in two Spanish catchments: Arás and Aguilón

The program Simulation of Hydrological Extreme Events provides a set of functionalities that combined together allows constructing, manipulating, analyzing and comparing the hydrological processes involved in flash flood generation. The program makes use of existing databases of interest in hydrology and available in Spain, such as digital terrain models, coverage of rainfall or curve number. Two pilot watersheds from Spain were selected, Arás and Aguilón, where flash flood episodes have taken place. A sensitivity analysis of the flash flood episodes in response to changes in the main hydrological processes involved has been made, such as spatial and temporal distribution of rainfall, soil moisture status and water flow through channel network. In this work, we found that the antecedent moisture condition is the most influential factor in the magnitude of flash floods produced by the same amount of rain. The temporal distribution of the storm represents the second characteristic in order of relevance. In addition, terrain morphology (specially the slope) is found to be decisive in the results differences obtained.

Developing and programming a watershed traversal algorithm (WTA) in GRID-DEM and adapting it to hydrological processes

A methodology for programming hydrological processes into watersheds using grid-type digital elevation models (DEMs) is investigated. This methodology is based on the basic configuration of the flow directions structure in the DEM, which is stored in files where information about topological relations and other frequently used features are saved. Some basic functions for managing topological data that significantly simplify the source code programming are also presented and described. We develop an algorithm that runs the entire drainage network in a watershed in both directions, upwards and downwards, which is ideal for incorporating structural models of hydrological processes that occur in basins or assessing its characteristics. The main attribute of this method is that information about hydrological processes and properties is transmitted during the routing from one area to another of the basin. The information is used when developing models of these hydrological processes and transmitted throughout the basin. At the end of the article, using this methodology with the SHEE software is illustrated with some examples.

Smartphone-camera-acquired pulse photoplethysmographic signal for deriving respiratory rate

A method for deriving respiratory rate from smartphone-camera-acquired pulse photoplethysmographic (SCPPG) signal is presented. It combines information from three derived respiration signals based on pulse width, amplitude, and rate variability (PWV, PAV, and PRV). Evaluation is performed over a database containing SCPPG signals recorded from 10 healthy subjects during controlled respiration experiments at rates from 0.2 to 0.6 Hz with a step of 0.1 Hz, using iPhone 4S device. Results suggest that habitual spontaneous respiratory rates (0.2-0.4 Hz) can be estimated from SCPPG signals by PWV and by PRV with low relative error (median of order 0.5% and IQR of order 2%). PWV method maintained its performance at rates up to 0.5 Hz, and the accuracy can be improved by combining it with other methods such as PRV and PAV.

Cross Time-Frequency Analysis for Combining Information of Several Sources: Application to Estimation of Spontaneous Respiratory Rate from Photoplethysmography

A methodology that combines information from several nonstationary biological signals is presented. This methodology is based on time-frequency coherence, that quantifies the similarity of two signals in the time-frequency domain. A cross time-frequency analysis method, based on quadratic time-frequency distribution, has been used for combining information of several nonstationary biomedical signals. In order to evaluate this methodology, the respiratory rate from the photoplethysmographic (PPG) signal is estimated. The respiration provokes simultaneous changes in the pulse interval, amplitude, and width of the PPG signal. This suggests that the combination of information from these sources will improve the accuracy of the estimation of the respiratory rate. Another target of this paper is to implement an algorithm which provides a robust estimation. Therefore, respiratory rate was estimated only in those intervals where the features extracted from the PPG signals are linearly coupled. In 38 spontaneous breathing subjects, among which 7 were characterized by a respiratory rate lower than 0.15 Hz, this methodology provided accurate estimates, with the median error {0.00; 0.98} mHz ({0.00; 0.31}%) and the interquartile range error {4.88; 6.59} mHz ({1.60; 1.92}%). The estimation error of the presented methodology was largely lower than the estimation error obtained without combining different PPG features related to respiration.

A city scale study on the effects of intensive groundwater heat pump systems on heavy metal contents in groundwater.

As a result of the increasing use of shallow geothermal resources, hydraulic, thermal and chemical impacts affecting groundwater quality can be observed with ever increasing frequency (Possemiers et al., 2014). To overcome the uncertainty associated with chemical impacts, a city scale study on the effects of intensive geothermal resource use by groundwater heat pump systems on groundwater quality, with special emphasis on heavy metal contents was performed. Statistical analysis of geochemical data obtained from several field campaigns has allowed studying the spatiotemporal relationship between temperature anomalies in the aquifer and trace element composition of groundwater. The relationship between temperature and the concentrations of trace elements resulted in weak correlations, indicating that temperature changes are not the driving factor in enhancing heavy metal contaminations. Regression models established for these correlations showed a very low reactivity or response of heavy metal contents to temperature changes. The change rates of heavy metal contents with respect to temperature changes obtained indicate a low risk of exceeding quality threshold values by means of the exploitation regimes used, neither producing nor enhancing contamination significantly. However, modification of pH, redox potential, electrical conductivity, dissolved oxygen and alkalinity correlated with the concentrations of heavy metals. In this case, the change rates of heavy metal contents are higher, with a greater risk of exceeding threshold values.