Evaluation of the risk associated with karstic processes in Miocene gypsum in south-eastern Madrid (Spain)

Relief formations characteristic of karstification processes affecting the Miocene gypsum formations existing in south-eastern Madrid have been discovered in that area of the city. These relief formations can pose significant risks to future urban development plans.The purpose of this article is to present an integrated model created from a geomorphological analysis of south-eastern Madrid through aerial photographs, geophysical inspections (microgravimetry) and geotechnical studies (in situ drilling and testing), in order to identify and measure the morphologies associated with karstic processes whose locations, dimensions and geotechnical characteristics are prone to causing damages that could pose a potential risk. The risk analysis is based on a study of the risk factors, focusing on vulnerability and the measurement of structural mitigation measures capable of preventing the damages that could be caused by the interaction between structural foundations and the morphological consequences of karstic processes on the soil.Ocena tveganj povezanih z zakrasevanjem miocenske sadre v jugovzhodnem Madridu (Španija)V jugovzhodnem Madridu je veliko reliefnih oblik, ki kažejo na zakrasevanje miocenske sadre. To predstavlja tveganje, ki ga moramo upoštevati pri urbanističnem načrtovanju. V članku predstavljamo celovit pristop, ki temelji na geomorfoloških analizah aeroposnetkov, mikrogravimetričnih in geotehničnih raziskavah, s katerim smo zaznali in izmerili morfološke značilnosti, ki so povezane z aktivnim zakrasevanjem sadre. Analiza tveganj temelji na študiji dejavnikov tveganja in se osredotoča na ranljivost in oceno uspešnosti strukturnih ukrepov za blažitev vpliva zakrasevanja v prsti na strukturne temelje

Positive airway pressure and electrical stimulation methods for obstructive sleep apnea treatment: a patent review (2005-2014)

Producción CientíficaIntroduction. Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a major health problem with significant negative effects on the health and quality of life. Continuous positive airway pressure (CPAP) is currently the primary treatment option and it is considered the most effective therapy for OSAHS. Nevertheless, comfort issues due to improper fit to patient’s changing needs and breathing gas leakage limit the patient’s adherence to treatment. Areas covered. The present patent review describes recent innovations in the treatment of OSAHS related to optimization of the positive pressure delivered to the patient, methods and systems for continuous self-adjusting pressure during inspiration and expiration phases, and techniques for electrical stimulation of nerves and muscles responsible for the airway patency. Expert opinion. In the last years, CPAP-related inventions have mainly focused on obtaining an optimal self-adjusting pressure according to patient’s needs. Despite intensive research carried out, treatment compliance is still a major issue. Hypoglossal electrical nerve stimulation could be an effective secondary treatment option when CPAP primary therapy fails. Several patents have been granted focused on selective stimulation techniques and parameter optimization of the stimulating pulse waveform. Nevertheless, there remain important issues to address, like effectiveness and adverse events due to improper stimulation.Ministerio de Economía y Competitividad (TEC2011-22987)Junta de Castilla y León (VA059U13

Utility of AdaBoost to Detect Sleep Apnea-Hypopnea Syndrome From Single-Channel Airflow

Producción CientíficaThe purpose of this study is to evaluate the usefulness of the boosting algorithm AdaBoost (AB) in the context of the sleep apnea-hypopnea syndrome (SAHS) diagnosis. Methods: We characterize SAHS in single-channel airflow (AF) signals from 317 subjects by the extraction of spectral and non-linear features. Relevancy and redundancy analyses are conducted through the fast correlation-based filter (FCBF) to derive the optimum set of features among them. These are used to feed classifiers based on linear discriminant analysis (LDA) and classification and regression trees (CART). LDA and CART models are sequentially obtained through AB, which combines their performances to reach higher diagnostic ability than each of them separately. Results: Our AB-LDA and AB-CART approaches showed high diagnostic performance when determining SAHS and its severity. The assessment of different apnea-hypopnea index cutoffs using an independent test set derived into high accuracy: 86.5% (5 events/h), 86.5% (10 events/h), 81.0% (15 events/h), and 83.3% (30 events/h). These results widely outperformed those from logistic regression and a conventional event-detection algorithm applied to the same database. Conclusion: Our results suggest that AB applied to data from single-channel AF can be useful to determine SAHS and its severity. Significance: SAHS detection might be simplified through the only use of single-channel AF data.Ministerio de Economía y Competitividad (project TEC2011-22987)Junta de Castilla y León (project VA059U13

Reconocimiento y registro 3D de objetos conocidos en una escena

El proyecto se inicia con la reconstrucción densa de una escena 3D a partir de imágenes en dos pasos. Con el primero de ellos se obtendrá la posición 3D de las cámaras usando la técnica conocida como Bundle Adjustment. En un segundo paso, a partir de estas localizaciones y mediante restricciones proyectivas se densificará la reconstrucción 3D de la escena. En esta primera fase del proyecto se desarrollará un visor 3D el cual nos permitirá manipular y visualizar el entorno 3D obtenido a partir de los programas mencionados previamente y que nos será de utilidad para la aplicación final. La segunda fase del proyecto se plantea el reconocimiento de objetos a partir de imágenes. El reconocimiento se realizará basado en características salientes en la imagen. En primer lugar se creará una pequeña base de datos con imágenes de un conjunto de objetos y su reconstrucción densa. En segundo lugar, se buscará en la escena los objetos de la base de datos mediante la comparación de descriptores asociados a las características salientes. Para ello será necesario el desarrollo de una aplicación que nos permita comparar las imágenes de los diferentes objetos de nuestra base de datos con las imágenes de la escena y ver así si los objetos de la base de datos aparecen o no en la escena. Una vez el objeto ha sido reconocido en la escena se pretende sustituir en el modelo 3D de dicha escena la reconstrucción 3D del objeto (por ejemplo, un libro) disponible en nuestra base de datos, permitiéndonos así visualizar en la escena 3D partes del libro que no se veían en las imágenes de la escena. Para ello será necesaria una tercera y última fase en el proyecto donde se deberá posicionar los modelos 3D de los objetos que disponemos en la base de datos y que aparecen en la escena

Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome

The relationship between sleep apnoea–hypopnoea syndrome (SAHS) severity and the regularity of nocturnal oxygen saturation (SaO2) recordings was analysed. Three different methods were proposed to quantify regularity: approximate entropy (AEn), sample entropy (SEn) and kernel entropy (KEn). A total of 240 subjects suspected of suffering from SAHS took part in the study. They were randomly divided into a training set (96 subjects) and a test set (144 subjects) for the adjustment and assessment of the proposed methods, respectively. According to the measurements provided by AEn, SEn and KEn, higher irregularity of oximetry signals is associated with SAHS-positive patients. Receiver operating characteristic (ROC) and Pearson correlation analyses showed that KEn was the most reliable predictor of SAHS. It provided an area under the ROC curve of 0.91 in two-class classification of subjects as SAHS-negative or SAHS-positive. Moreover, KEn measurements from oximetry data exhibited a linear dependence on the apnoea–hypopnoea index, as shown by a correlation coefficient of 0.87. Therefore, these measurements could be used for the development of simplified diagnostic techniques in order to reduce the demand for polysomnographies. Furthermore, KEn represents a convincing alternative to AEn and SEn for the diagnostic analysis of noisy biomedical signals

Assessment of Time and Frequency Domain Entropies to Detect Sleep Apnoea in Heart Rate Variability Recordings from Men and Women

Producción CientíficaHeart rate variability (HRV) provides useful information about heart dynamics both under healthy and pathological conditions. Entropy measures have shown their utility to characterize these dynamics. In this paper, we assess the ability of spectral entropy (SE) and multiscale entropy (MsE) to characterize the sleep apnoea-hypopnea syndrome (SAHS) in HRV recordings from 188 subjects. Additionally, we evaluate eventual differences in these analyses depending on the gender. We found that the SE computed from the very low frequency band and the low frequency band showed ability to characterize SAHS regardless the gender; and that MsE features may be able to distinguish gender specificities. SE and MsE showed complementarity to detect SAHS, since several features from both analyses were automatically selected by the forward-selection backward-elimination algorithm. Finally, SAHS was modelled through logistic regression (LR) by using optimum sets of selected features. Modelling SAHS by genders reached significant higher performance than doing it in a jointly way. The highest diagnostic ability was reached by modelling SAHS in women. The LR classifier achieved 85.2% accuracy (Acc) and 0.951 area under the ROC curve (AROC). LR for men reached 77.6% Acc and 0.895 AROC, whereas LR for the whole set reached 72.3% Acc and 0.885 AROC. Our results show the usefulness of the SE and MsE analyses of HRV to detect SAHS, as well as suggest that, when using HRV, SAHS may be more accurately modelled if data are separated by gender.Ministerio de Economía, Industria y Competitividad (TEC2011-22987)Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA059U13

Evaluation of Machine-Learning Approaches to Estimate Sleep Apnea Severity from at-Home Oximetry Recordings

Producción CientíficaComplexity, costs, and waiting lists issues demand a simplified alternative for sleep apnea-hypopnea syndrome (SAHS) diagnosis. The blood oxygen saturation signal (SpO2) carries useful information about SAHS and can be easily acquired from overnight oximetry. In this study, SpO2 single-channel recordings from 320 subjects were obtained at patients’ home. They were used to automatically obtain statistical, spectral, non-linear, and clinical SAHS-related information. Relevant and non-redundant data from these analyses were subsequently used to train and validate four machine-learning methods with ability to classify SpO2 signals into one out of the four SAHS-severity degrees (no-SAHS, mild, moderate, and severe). All the models trained (linear discriminant analysis, 1-vs-all logistic regression, Bayesian multi-layer perceptron, and AdaBoost), outperformed the diagnostic ability of the conventionally-used 3% oxygen desaturation index. An AdaBoost model built with linear discriminants as base classifiers reached the highest figures. It achieved 0.479 Cohen’s in the SAHS severity classification, as well as 92.9%, 87.4%, and 78.7% accuracies in binary classification tasks using increasing severity thresholds (apnea-hypopnea index: 5, 15, and 30 events/hour, respectively). These results suggest that machine learning can be used along with SpO2 information acquired at patients’ home to help in SAHS diagnosis simplification.This research has been supported by the project VA037U16 from the Consejería de Educación de la Junta de Castilla y León, the project 265/2012 of the Sociedad Española de Neumología y Cirugía Torácica (SEPAR), the projects RTC-2015-3446-1 and TEC2014-53196-R from the Ministerio de Economía y Competitividad, and the European Regional Development Fund (FEDER). D. Álvarez was in receipt of a Juan de la Cierva grant from the Ministerio de Economía y Competitivida

Acrocéfalo-sindactilia tipo i. síndrome de apert presentación de un caso

Acrocefalosindactilia tipo I o síndrome de Apert es un síndrome que se caracteriza por el cierre prematuro de las suturas craneales, lo que hace que la cabeza tome una forma puntiaguda y que se deforme la apariencia de la cara por anomalía craneofacial que se produce por malformaciones en cráneo, cara, manos y pies, además de diversas alteraciones funcionales que varían mucho de unos niños a otros. La incidencia es de 1´2 por cada 100000 nacidos vivos, es una rareza médica y un síndrome en el cual los factores de riesgo hereditarios y ambientales como la edad del padre juegan un papel etiológico Se presenta a un adolescente que consulta por deformaciones de los arcos dentarios superior e inferior, acompañados con otros signos cráneo - cefálicos, como son la cabeza puntiaguda y deformaciones faciales, así como malformaciones de manos y pies siendo portador de un síndrome de Apert. Motivados por la rareza clínica de esta entidad y las complicaciones potencialmente evitables con un diagnóstico precoz se decidió dar a conocer este caso