Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

A syntactic approach to combining functional notation, lazy evaluation, and higher-order in LP systems

Nondeterminism and partially instantiated data structures give logic programming expressive power beyond that of functional programming. However, functional programming often provides convenient syntactic features, such as having a designated implicit output argument, which allow function cali nesting and sometimes results in more compact code. Functional programming also sometimes allows a more direct encoding of lazy evaluation, with its ability to deal with infinite data structures. We present a syntactic functional extensión, used in the Ciao system, which can be implemented in ISO-standard Prolog systems and covers function application, predefined evaluable functors, functional definitions, quoting, and lazy evaluation. The extensión is also composable with higher-order features and can be combined with other extensions to ISO-Prolog such as constraints. We also highlight the features of the Ciao system which help implementation and present some data on the overhead of using lazy evaluation with respect to eager evaluation.

Hiord: A type-free higher-order logic programming language with predicate abstraction

A new formalism, called Hiord, for defining type-free higherorder logic programming languages with predicate abstraction is introduced. A model theory, based on partial combinatory algebras, is presented, with respect to which the formalism is shown sound. A programming language built on a subset of Hiord, and its implementation are discussed. A new proposal for defining modules in this framework is considered, along with several examples.

Kinematic and heart rate demands in 4x4 vs 7x7 small sided games in professional soccer players

Comparación de las variables cinemáticas y de frecuencia cardiaca en dos posesiones en fútbol

Higher-order regularization and morphological techniques for image segmentation

La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

Heart rate recovery in elite Spanish male athletes

Recuperación de la frecuencia cardiaca en atletas varones españoles During postexercise recovery, heart rate (HR) initially falls rapidly, followed by a period of slower decrease, until resting values are reached. The aim of the present work was to examine the differences in the recovery heart rate (RHR) between athletes engaged in static and dynamic sports.

Steady-state thermal analysis of an innovative receiver for linear Fresnel reflectors

The study of the performance of an innovative receiver for linear Fresnel reflectors is carried out in this paper, and the results are analyzed with a physics perspective of the process. The receiver consists of a bundle of tubes parallel to the mirror arrays, resulting on a smaller cross section for the same receiver width as the number of tubes increases, due to the diminution of their diameter. This implies higher heat carrier fluid speeds, and thus, a more effective heat transfer process, although it conveys higher pumping power as well. Mass flow is optimized for different tubes diameters, different impinging radiation intensities and different fluid inlet temperatures. It is found that the best receiver design, namely the tubes diameter that maximizes the exergetic efficiency for given working conditions, is similar for the cases studied. There is a range of tubes diameters that imply similar efficiencies, which can drive to capital cost reduction thanks to the flexibility of design. In addition, the length of the receiver is also optimized, and it is observed that the optimal length is similar for the working conditions considered. As a result of this study, it is found that this innovative receiver provides an optimum design for the whole day, even though impinging radiation intensity varies notably. Thermal features of this type of receiver could be the base of a new generation of concentrated solar power plants with a great potential for cost reduction, because of the simplicity of the system and the lower weigh of the components, plus the flexibility of using the receiver tubes for different streams of the heat carrier fluid.

Order 10 4 speedup in global linear instability analysis using matrix formation

A unified solution framework is presented for one-, two- or three-dimensional complex non-symmetric eigenvalue problems, respectively governing linear modal instability of incompressible fluid flows in rectangular domains having two, one or no homogeneous spatial directions. The solution algorithm is based on subspace iteration in which the spatial discretization matrix is formed, stored and inverted serially. Results delivered by spectral collocation based on the Chebyshev-Gauss-Lobatto (CGL) points and a suite of high-order finite-difference methods comprising the previously employed for this type of work Dispersion-Relation-Preserving (DRP) and Padé finite-difference schemes, as well as the Summationby- parts (SBP) and the new high-order finite-difference scheme of order q (FD-q) have been compared from the point of view of accuracy and efficiency in standard validation cases of temporal local and BiGlobal linear instability. The FD-q method has been found to significantly outperform all other finite difference schemes in solving classic linear local, BiGlobal, and TriGlobal eigenvalue problems, as regards both memory and CPU time requirements. Results shown in the present study disprove the paradigm that spectral methods are superior to finite difference methods in terms of computational cost, at equal accuracy, FD-q spatial discretization delivering a speedup of ð (10 4). Consequently, accurate solutions of the three-dimensional (TriGlobal) eigenvalue problems may be solved on typical desktop computers with modest computational effort.

Adaptaciones cardiacas hemodinámicas, estructurales y funcionales a un programa de ejercicio físico supervisado durante el embarazo: ensayo clínico aleatorizado = Hemodynamic, structural and functional cardiac adaptations in a supervised physical exercise program during pregnancy: a randomized controlled trial

Introducción: Diversos cambios ocurren en el sistema cardiovascular materno durante el embarazo, lo que genera un gran estrés sobre este sistema especialmente durante el tercer trimestre, pudiendo acentuarse en presencia de determinados factores de riesgo. Los objetivos de este estudio fueron, valorar las adaptaciones cardiovasculares producidas por un programa específico de ejercicio físico; su seguridad sobre el sistema cardiovascular materno y los resultados del embarazo; y su eficacia en el control de los factores de riesgo cardiovascular. Material y métodos: El diseño del estudio fue un ensayo clínico aleatorizado. 151 gestantes sanas fueron evaluadas mediante un ecocardiograma y un electrocardiograma en la semana 20 y 34 de gestación. Un total de 89 gestantes participaron en un programa de ejercicio físico (GE) desde el primer hasta el tercer trimestre de embarazo, constituido principalmente por 25-30 minutos de trabajo aeróbico (55-60% de la frecuencia cardiaca de reserva), trabajo de fortalecimiento general y específico, y un trabajo de tonificación del suelo pélvico; desarrollado 3 días a la semana con una duración de 55-60 minutos cada sesión. Las gestantes aleatoriamente asignadas al grupo de control (GC; n=62) permanecieron sedentarias durante el embarazo. El estudio fue aprobado por el Comité Ético de investigación clínica del Hospital Universitario de Fuenlabrada. Resultados: Las características basales fueron similares entre ambos grupos. A diferencia del GC, las gestantes del GE evitaron el descenso significativo del gasto cardiaco indexado, entre el 2º y 3ºT de embarazo, y conservaron el patrón geométrico normal del ventrículo izquierdo; mientras que en el GC cambió hacia un patrón de remodelado concéntrico. En la semana 20, las gestantes del GE presentaron valores significativamente menores de frecuencia cardiaca (GC: 79,56±10,76 vs. GE: 76,05±9,34; p=0,04), tensión arterial sistólica (GC: 110,19±10,23 vs. GE: 106,04±12,06; p=0,03); tensión arterial diastólica (GC: 64,56±7,88 vs. GE: 61,81±7,15; p=0,03); tiempo de relajación isovolumétrica (GC: 72,94±14,71 vs. GE: 67,05±16,48; p=0,04); y un mayor tiempo de deceleración de la onda E (GC: 142,09±39,11 vs. GE: 162,10±48,59; p=0,01). En la semana 34, el GE presentó valores significativamente superiores de volumen sistólico (GC: 51,13±11,85 vs. GE: 56,21±12,79 p=0,04), de llenado temprano del ventrículo izquierdo (E) (GC: 78,38±14,07 vs. GE: 85,30±16,62; p=0,02) y de tiempo de deceleración de la onda E (GC: 130,35±37,11 vs. GE: 146,61±43,40; p=0,04). Conclusión: La práctica regular de ejercicio físico durante el embarazo puede producir adaptaciones positivas sobre el sistema cardiovascular materno durante el tercer trimestre de embarazo, además de ayudar en el control de sus factores de riesgo, sin alterar la salud materno-fetal. ABSTRACT Background: Several changes occur in the maternal cardiovascular system during pregnancy. These changes produce a considerable stress in this system, especially during the third trimester, which can be increased in presence of some risk factors. The aims of this study were, to assess the maternal cardiac adaptations in a specific exercise program; its safety on the maternal cardiovascular system and pregnancy outcomes; and its effectiveness in the control of cardiovascular risk factors. Material and methods: A randomized controlled trial was designed. 151 healthy pregnant women were assessed by an echocardiography and electrocardiography at 20 and 34 weeks of gestation. A total of 89 pregnant women participated in a physical exercise program (EG) from the first to the third trimester of pregnancy. It consisted of 25-30 minutes of aerobic conditioning (55-60% of their heart rate reserve), general and specific strength exercises, and a pelvic floor muscles training; 3 times per weeks during 55-60 minutes per session. Pregnant women randomized allocated to the control group (CG) remained sedentary during pregnancy. The study was approved by the Research Ethics Committee of Hospital Universitario de Fuenlabrada. Results: Baseline characteristics were similar between groups. Difference from the CG, pregnant women from the EG prevented the significant decrease of the cardiac output index, between the 2nd and 3rd trimester of pregnancy, and preserved the normal left ventricular pattern; whereas in the CG shifted to concentric remodeling pattern. At 20 weeks, women in the EG had significant lower heart rate (CG: 79,56±10,76 vs. EG: 76,05±9,34; p=0,04), systolic blood pressure (CG: 110,19±10,23 vs. EG: 106,04±12,06; p=0,03); diastolic blood pressure (CG: 64,56±7,88 vs. EG: 61,81±7,15; p=0,03); isovolumetric relaxation time (GC: 72,94±14,71 vs. GE: 67,05±16,48; p=0,04); and a higher deceleration time of E Wave (GC: 142,09±39,11 vs. GE: 162,10±48,59; p=0,01). At 34 weeks, the EG had a significant higher stroke volume (CG: 51,13±11,85 vs. EG: 56,21±12,79 p=0,04), early filling of left ventricular (E) (CG: 78,38±14,07 vs. EG: 85,30±16,62; p=0,02) and deceleration time of E wave (CG: 130,35±37,11 vs. EG:146,61±43,40; p=0,04). Conclusion: Physical regular exercise program during pregnancy may produce positive maternal cardiovascular adaptations during the third trimester of pregnancy. In addition, it helps to control the cardiovascular risk factors without altering maternal and fetus health.