Traditional and novel methods for occlusal caries detection: performance on primary teeth

This study aimed to assess the performance of International Caries Detection and Assessment System (ICDAS), radiographic examination, and fluorescence-based methods for detecting occlusal caries in primary teeth. One occlusal site on each of 79 primary molars was assessed twice by two examiners using ICDAS, bitewing radiography (BW), DIAGNOdent 2095 (LF), DIAGNOdent 2190 (LFpen), and VistaProof fluorescence camera (FC). The teeth were histologically prepared and assessed for caries extent. Optimal cutoff limits were calculated for LF, LFpen, and FC. At the D (1) threshold (enamel and dentin lesions), ICDAS and FC presented higher sensitivity values (0.75 and 0.73, respectively), while BW showed higher specificity (1.00). At the D (2) threshold (inner enamel and dentin lesions), ICDAS presented higher sensitivity (0.83) and statistically significantly lower specificity (0.70). At the D(3) threshold (dentin lesions), LFpen and FC showed higher sensitivity (1.00 and 0.91, respectively), while higher specificity was presented by FC (0.95), ICDAS (0.94), BW (0.94), and LF (0.92). The area under the receiver operating characteristic (ROC) curve (Az) varied from 0.780 (BW) to 0.941 (LF). Spearman correlation coefficients with histology were 0.72 (ICDAS), 0.64 (BW), 0.71 (LF), 0.65 (LFpen), and 0.74 (FC). Inter- and intraexaminer intraclass correlation values varied from 0.772 to 0.963 and unweighted kappa values ranged from 0.462 to 0.750. In conclusion, ICDAS and FC exhibited better accuracy in detecting enamel and dentin caries lesions, whereas ICDAS, LF, LFpen, and FC were more appropriate for detecting dentin lesions on occlusal surfaces in primary teeth, with no statistically significant difference among them. All methods presented good to excellent reproducibility.

Establishing optimal quantitative-polymerase chain reaction assays for routine diagnosis and tracking of minimal residual disease in JAK2-V617F-associated myeloproliferative neoplasms: a joint European LeukemiaNet/MPN&MPNr-EuroNet (COST action BM0902) study.

Reliable detection of JAK2-V617F is critical for accurate diagnosis of myeloproliferative neoplasms (MPNs); in addition, sensitive mutation-specific assays can be applied to monitor disease response. However, there has been no consistent approach to JAK2-V617F detection, with assays varying markedly in performance, affecting clinical utility. Therefore, we established a network of 12 laboratories from seven countries to systematically evaluate nine different DNA-based quantitative PCR (qPCR) assays, including those in widespread clinical use. Seven quality control rounds involving over 21,500 qPCR reactions were undertaken using centrally distributed cell line dilutions and plasmid controls. The two best-performing assays were tested on normal blood samples (n=100) to evaluate assay specificity, followed by analysis of serial samples from 28 patients transplanted for JAK2-V617F-positive disease. The most sensitive assay, which performed consistently across a range of qPCR platforms, predicted outcome following transplant, with the mutant allele detected a median of 22 weeks (range 6-85 weeks) before relapse. Four of seven patients achieved molecular remission following donor lymphocyte infusion, indicative of a graft vs MPN effect. This study has established a robust, reliable assay for sensitive JAK2-V617F detection, suitable for assessing response in clinical trials, predicting outcome and guiding management of patients undergoing allogeneic transplant.

Privacy-Preserving Optimal Meeting Location Determination on Mobile Devices

Equipped with state-of-the-art smartphones and mobile devices, today's highly interconnected urban population is increasingly dependent on these gadgets to organize and plan their daily lives. These applications often rely on current (or preferred) locations of individual users or a group of users to provide the desired service, which jeopardizes their privacy; users do not necessarily want to reveal their current (or preferred) locations to the service provider or to other, possibly untrusted, users. In this paper, we propose privacy-preserving algorithms for determining an optimal meeting location for a group of users. We perform a thorough privacy evaluation by formally quantifying privacy-loss of the proposed approaches. In order to study the performance of our algorithms in a real deployment, we implement and test their execution efficiency on Nokia smartphones. By means of a targeted user-study, we attempt to get an insight into the privacy-awareness of users in location-based services and the usability of the proposed solutions.

Therapeutic drug monitoring of once daily aminoglycoside dosing: comparison of two methods and investigation of the optimal blood sampling strategy.

PURPOSE Therapeutic drug monitoring of patients receiving once daily aminoglycoside therapy can be performed using pharmacokinetic (PK) formulas or Bayesian calculations. While these methods produced comparable results, their performance has never been checked against full PK profiles. We performed a PK study in order to compare both methods and to determine the best time-points to estimate AUC0-24 and peak concentrations (C max). METHODS We obtained full PK profiles in 14 patients receiving a once daily aminoglycoside therapy. PK parameters were calculated with PKSolver using non-compartmental methods. The calculated PK parameters were then compared with parameters estimated using an algorithm based on two serum concentrations (two-point method) or the software TCIWorks (Bayesian method). RESULTS For tobramycin and gentamicin, AUC0-24 and C max could be reliably estimated using a first serum concentration obtained at 1 h and a second one between 8 and 10 h after start of the infusion. The two-point and the Bayesian method produced similar results. For amikacin, AUC0-24 could reliably be estimated by both methods. C max was underestimated by 10-20% by the two-point method and by up to 30% with a large variation by the Bayesian method. CONCLUSIONS The ideal time-points for therapeutic drug monitoring of once daily administered aminoglycosides are 1 h after start of a 30-min infusion for the first time-point and 8-10 h after start of the infusion for the second time-point. Duration of the infusion and accurate registration of the time-points of blood drawing are essential for obtaining precise predictions.

In vitro performance of a pen-type laser fluorescence device and bitewing radiographs for approximal caries detection in permanent and primary teeth.

AIM To evaluate the performance of a pen‑type laser fluorescence device (DIAGNOdent 2190; LFpen, KaVo, Germany) and bitewing radiographs (BW) for approximal caries detection in permanent and primary teeth. MATERIALS AND METHODS A total of 246 anterior approximal surfaces (102 permanent and 144 primary) were selected. Contact points were simulated using sound teeth. Two examiners assessed all approximal surfaces using LFpen and BW. The teeth were histologically assessed for the reference standard. Optimal cut‑off limits were calculated for LFpen for primary and permanent teeth. Sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (Az) were calculated for D1 (enamel and dentin lesions) and D3 (dentin lesions) thresholds. The reproducibility was assessed by intraclass correlation coefficient (ICC) and Cohen's weighted kappa values. RESULTS For permanent teeth, the LFpen cut‑off were 0- 27 (sound), 28- 33 (enamel caries) and >33 (dentin caries). For primary teeth, the LFpen cut‑off were 0- 7 (sound), 8- 32 (enamelcaries) and >32 (dentin caries). The LFpen presented higher sensitivity values than BW for primary teeth (0.58 vs. 0.32 at D1 and 0.80 vs. 0.47 at D3) and permanent teeth (0.80 vs. 0.57 at D1 and 0.94 vs. 0.51 at D3). Specificity did not show a significant difference between the methods. Rank correlations with histology were 0.59 and 0.83 (LFpen) and 0.36 and 0.70 (BW) for primary and permanent teeth, respectively, considering all lesions. ICC values for LFpen were 0.71 (inter) and 0.86 (intra) for permanent teeth and 0.94 (inter) and 0.90/0.99 for primary teeth. Kappa values for BW were 0.69 (inter) and 0.68/0.90 (intra) for permanent teeth and 0.64 (inter) and 0.89/0.89 for primary teeth. CONCLUSION LFpen presented better reproducibility for primary and permanent teeth and higher accuracy in detecting caries lesions at D1 threshold than BW for permanent teeth. LFpen should be used as an adjunct method for approximal caries detection.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Ego depletion and persistent performance in a cycling task

We tested the assumption that persistent performance in an exhausting indoor cycling task would depend on momentarily available self-control strength (N = 20 active participants). In a within-subjects design (two points of measurement, exactly seven days apart), participants’ self-control strength was experimentally manipulated (depletion: yes vs. no; order counterbalanced) via the Stroop test before the participants performed a cycling task. In line with our hypothesis, hierarchical linear modelling (HLM) revealed that participants consistently performed worse over a period of 18 minutes when they were ego depleted. In addition, HLM analysis revealed that depleted participants invested less effort in the cycling task, as indicated by their lower heart rate. This effect escalated over time, as indicated by a time × condition interaction. These results indicate that self-control strength is necessary to obtain an optimal level of performance in endurance tasks requiring high levels of persistence. Practical implications are discussed.

Cerebellar Pathology Does Not Impair Performance on Identification or Categorization Tasks

In comparison to the basal ganglia, prefrontal cortex, and medial temporal lobes, the cerebellum has been absent from recent research on the neural substrates of categorization and identification, two prominent tasks in the learning and memory literature. To investigate the contribution of the cerebellum to these tasks, we tested patients with cerebellar pathology (seven with bilateral degeneration, six with unilateral lesions, and two with midline damage) on rule-based and information-integration categorization tasks and an identification task. In rule-based tasks, it is assumed that participants learn the categories through an explicit reasoning process. In information-integration tasks, optimal performance requires the integration of information from multiple stimulus dimensions, and participants are typically unaware of the decision strategy. The identification task, in contrast, required participants to learn arbitrary, color-word associations. The cerebellar patients performed similar to matched controls on all three tasks and performance did not vary with the extent of cerebellar pathology. Although the interpretation of these null results requires caution, these data contribute to the current debate on cerebellar contributions to cognition by providing boundary conditions on understanding the neural substrates of categorization and identification, and help define the functional domain of the cerebellum in learning and memory.

Optimizing Performance of Conductive Nanoparticle-filled Membranes

Conductive membranes were prepared by magnetic alignment of graphite-coated iron nanoparticles (GCINs) in a polyisobutylene (PIB) matrix, which was cast onto an interdigitated surface electrode. Toluene and tetrahydrofuran (THF) were used as solvents for the casting solution. Different molecular weights of PIB and solutions with concentrations ranging from 0.05- to 50-wt% were explored to optimize the mechanical and physical properties of the membrane. The amount of GCINs used in the membranes ranged from 0.1- to 2.5-wt%, and a sonicator was used to disperse the particles in the membrane. Sedimentation and surfactant studies were conducted to investigate the dispersion of GCINs in solutions. Progresses were made to find an optimal combination of various parameters in order to attain thin homogenous membranes for fast response.

Experiment: Combined effects of CO2, temperature, irradiance and time on the physiological performance of Chondrus crispus (Rhodophyta)

In natural environments, marine biotas are exposed to a variety of simultaneously acting abiotic factors. Among these, temperature, irradiance and CO2 availability are major factors influencing the physiological performance of marine macroalgae. To test whether elevated levels of CO2 may remediate the otherwise reduced performance of uncalcified seaweeds under the influence of other stressful abiotic factors, we performed multifactorial experiments with the red alga Chondrus crispus from Helgoland (North Sea) with two levels of CO2, temperature and irradiance: low and high pCO2 levels were tested in combination with either (1) optimal and low irradiances or (2) optimal and sub-lethal high temperatures for growth. Performance of C. crispus was evaluated as biomass increase and relative growth rates (RGR), gross photosynthesis and pigment content. Acclimations of growth and photosynthesis were measured after 4 and 8 days. Acclimation time was crucial for elucidating single or combined CO2 effects on growth and photosynthesis. Signifi- cant CO2 effects became evident only in combination with either elevated temperature or reduced irradiance. Growth and photosynthesis had divergent patterns: RGR and biomass significantly increased only under a combination of high pCO2 and elevated temperature; gross photosynthesis was significantly reduced under high pCO2 conditions at low irradiance. Pigment content varied in response to irradiance and temperature, but was independent of pCO2.

Effects of increasing levels of pea hulls in the diet on productive performance, development of the gastrointestinal tract, and nutrient retention of broilers from one to eighteeen days of age

The effects of inclusion of pea hulls (PH) in the diet on growth performance, development of the gastrointestinal tract and nutrient retention were studied in broilers from 1 to 18d of age. There were a control diet based on low fibre ingredients (69.3 total dietary fibre (16.1g crude fibre/kg)) and three additional diets that resulted from the dilution of the basal diet with 25, 50 and 75g PH/kg (81.2, 93.2, and 105.1g total dietary fibre/kg diet, respectively). Each treatment was replicated six times and the experimental unit was a cage with 12 chicks. Growth performance, development of the gastrointestinal tract and the coefficients of total tract apparent retention (CTTAR) of nutrients were recorded at 6, 12 and 18d of age. In addition, jejunal morphology was measured at 12 and 18d and the coefficients of apparent ileal digestibility (CAID) of nutrients at 18d of age. Pea hulls inclusion affected all the parameters studied. The inclusion of 25 and 50g PH/kg diet improved growth performance as compared to the control diet. The relative weight (g/kg body weight) of proventriculus (P≤0.01), gizzard (P≤0.001) and ceca (P≤0.05) increased linearly as the level of PH in the diet increased. The inclusion of PH affected quadratically (P≤0.01) villus height:crypt depth ratio with the highest value shown at 25g PH/kg. In general, the CTTAR and CAID of nutrients increased linearly and quadratically (P≤0.05) with increasing levels of PH, showing maximum values with PH level between 25 and 50g/kg diet. We conclude that the size of the digestive organs increases with increasing levels of PH in the diet. In general, the best performance and nutrient digestibility values were observed with levels of PH within the range of 25 and 50g/kg. Therefore, young broilers have a requirement for a minimum amount of dietary fibre. When pea hulls are used as a source of fibre, the level of total dietary fibre required for optimal performance is within the range of 81.2–93.2g/kg diet (25.6–35.0g crude fibre/kg diet). An excess of total dietary fibre (above 93.2g/kg diet) might reduce nutrient digestibility and growth performance to values similar to those observed with the control diet.

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

Nutritional impact on health and performance in intensively reared rabbits

The present work summarizes research related to the definition of nutrient recommendations for feeds used in the intensive production of rabbit's meat. Fibre is the main chemical constituent of rabbit diets that typically contain 320 to 360 and 50 to 90 g/kg of insoluble and soluble fibre, respectively. Instead, the dietary contents of cereal grains (∼120 to 160 g/kg), fat (15 to 25 g/kg) and protein concentrates (150 to 180 g/kg) are usually low with respect to other intensively reared monogastric animals. Cell wall constituents are not well digested in rabbits, but this effect is compensated by its stimulus of gut motility, which leads to an increasing rate of passage of digesta, and allows achieving an elevated dry matter intake. A high feed consumption and an adequate balance in essential nutrients are required to sustain the elevated needs of high-productive rabbits measured either as reproductive yield, milk production or growth rate in the fattening period. Around weaning, pathologies occur in a context of incomplete development of the digestive physiology of young rabbits. The supply of balanced diets has also been related to the prevention of disorders by means of three mechanisms: (i) promoting a lower retention time of the digesta in the digestive tract through feeding fibre sources with optimal chemical and physical characteristics, (ii) restricting feed intake after weaning or (iii) causing a lower flow of easily available substrates into the fermentative area by modifying feed composition (e.g. by lowering protein and starch contents, increasing its digestibility or partially substituting insoluble with soluble fibre), or by delaying age at weaning. The alteration in the gut microbiota composition has been postulated as the possible primary cause of these pathologies.

Ion Beam Analysis of He-implanted fusion solid breedes

Introduction Lithium-based ceramics (silicates, titanates, ?) possess a series of advantages as alternative over liquid lithium and lithium-lead alloys for fusion breeders. They have a sufficient lithium atomic density (up to 540 kg*m-3), high temperature stability (up to 1300 K), and good chemical compatibility with structural materials. Nevertheless, few research is made on the diffusion behavior of He and H isotopes through polycrystalline structures of porous ceramics which is crucial in order to understand the mobility of gas coolants as well as, the release of tritium. Moreover, in the operating conditions of actual breeder blanket concepts, the extraction rate of the helium produced during lithium transmutation can be affected by the composition and the structure of the near surface region modifying the performance of BB materials

Localization and activity detection Based on the fusion of environment And inertial sensors = Localización y detección de actividad Basadas en integración de sensores y dispositivos inerciales

Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.