G-Sense: a scalable architecture for global sensing and monitoring

The pervasiveness of cellular phones combined with Internet connectivity, GPS embedded chips, location information, and integrated sensors provide an excellent platform to collect data about the individual and its surrounding environment. As a result, new applications have recently appeared to address large-scale societal problems as well as improve the quality of life of the individual. However, these new applications, recently called location-based services, participatory sensing, and human-centric sensing, bring many new challenges, one of them being the management of the huge amount of traffic (data) they generate. This article presents G-Sense, for Global-Sense, an architecture that integrates mobile and static wireless sensor networks in support of location-based services, participatory sensing, and human-centric sensing applications. G-Sense includes specific mechanisms to control the amount of data generated by these applications while meeting the application requirements. Furthermore, it creates a network of servers organized in a peer-to-peer architecture to address scalability and reliability issues. An example prototype application is presented along with some basic results and open research issues

Centinela: A human activity recognition system based on acceleration and vital sign data

This paper presents Centinela, a system that combines acceleration data with vital signs to achieve highly accurate activity recognition. Centinela recognizes five activities: walking, running, sitting, ascending, and descending. The system includes a portable and unobtrusive real-time data collection platform, which only requires a single sensing device and a mobile phone. To extract features, both statistical and structural detectors are applied, and two new features are proposed to discriminate among activities during periods of vital sign stabilization. After evaluating eight different classifiers and three different time window sizes, our results show that Centinela achieves up to 95.7% overall accuracy, which is higher than current approaches under similar conditions. Our results also indicate that vital signs are useful to discriminate between certain activities. Indeed, Centinela achieves 100% accuracy for activities such as running and sitting, and slightly improves the classification accuracy for ascending compared to the cases that utilize acceleration data only

¿Reducir el rango de comunicación o apagar nodos? Una evaluación inicial de estrategias para control de topología en redes inalámbricas de sensores

AbstractTopology control-TC is a strategy used to save energy in wireless sensor networks. Topology construction-TCn is the area of TC that studies the reduction of the network topology, while maintaining characteristics like connectivity and coverage. There are two main strategies to reduce the topology of a network: reducing the transmission power, like the KNEIGH-Tree, and decreasing the number of active nodes in the network, like A3 and A3Cov. Both strategies reduce the energy consumption and, therefore, increase the network lifetime; however, these strategies have not been compared against one another. This paper compares the three protocols mentioned before in terms of the network lifetime and coverage. The results show that in dense networks, the A3 and A3Cov protocols extend the lifetime of the network more than twice than that of the offered by the KNEIGH-Tree protocol.ResumenControl de Topología-(CT) es una estrategia para ahorrar energía en las redes inalámbricas de sensores. Construcción de Topología-(CnT) es el área de CT que estudia la reducción de la topología de la red, manteniendo características como cubrimiento y conectividad. Las dos principales estrategias existentes para CnT se basan en reducir la potencia de transmisión de los nodos, como el KNEIGH-Tree, o en disminuir el número de nodos activos, como A3 y A3Cov. Ambas estrategias reducen el consumo de energía en la red, extendiendo su vida útil; sin embargo, hasta ahora estas estrategias no se han comparado entre ellas. Este artículo evalúa los tres protocolos mencionados en términos de su impacto en la vida de la red y la cobertura de área. Los resultados en redes densas muestran que A3 y A3Cov superan en más de 100% los resultados de KNEIGH-Tree

Multi sensor system for pedestrian tracking and activity recognition in indoor environments

The widespread use of mobile devices and the rise of Global Navigation Satellite Systems (GNSS) have allowed mobile tracking applications to become very popular and valuable in outdoor environments. However, tracking pedestrians in indoor environments with Global Positioning System (GPS)-based schemes is still very challenging. Along with indoor tracking, the ability to recognize pedestrian behavior and activities can lead to considerable growth in location-based applications including pervasive healthcare, leisure and guide services (such as, hospitals, museums, airports, etc.), and emergency services, among the most important ones. This paper presents a system for pedestrian tracking and activity recognition in indoor environments using exclusively common off-the-shelf sensors embedded in smartphones (accelerometer, gyroscope, magnetometer and barometer). The proposed system combines the knowledge found in biomechanical patterns of the human body while accomplishing basic activities, such as walking or climbing stairs up and down, along with identifiable signatures that certain indoor locations (such as turns or elevators) introduce on sensing data. The system was implemented and tested on Android-based mobile phones. The system detects and counts steps with an accuracy of 97% and 96:67% in flat floor and stairs, respectively; detects user changes of direction and altitude with 98:88% and 96:66% accuracy, respectively; and recognizes the proposed human activities with a 95% accuracy. All modules combined lead to a total tracking accuracy of 91:06% in common human motion indoor displacement

Differential effects of tau stage, Lewy body pathology, and substantia nigra degeneration on FDG-PET patterns in clinical AD

PURPOSE: Comorbid Lewy body (LB) pathology is common in AD. The effect of LB co-pathology on FDG-PET patterns in AD is yet to be studied. We analysed associations of neuropathologically-assessed tau pathology, LB pathology, and substantia nigra neuron loss (SNnl) with ante-mortem FDG-PET hypometabolism in patients with a clinical AD presentation. METHODS: Twenty-one patients with autopsy-confirmed AD (‘pure-AD’), 24 with AD and LB co-pathology (‘AD-LB’), and 7 with LB but no or low evidence of AD pathology (‘pure-LB’) were studied. Pathologic groups were compared on regional and voxel-wise FDG-PET patterns, the cingulate island sign ratio (CISr), and neuropathological ratings of SNnl. Additional analyses assessed continuous associations of Braak tangle stage and SNnl with FDG-PET patterns. RESULTS: Pure-AD and AD-LB showed highly similar patterns of AD-typical temporo-parietal hypometabolism and did not differ in CISr, regional FDG SUVR, or SNnl. By contrast, pure-LB showed the expected DLB-like pattern, accompanied by pronounced occipital hypometabolism and elevated CISr and SNnl compared to the AD groups. In continuous analyses, Braak tangle stage was significantly correlated with more AD-like, and SNnl with more DLB-like, FDG-PET patterns. CONCLUSIONS: In autopsy-confirmed AD dementia patients, comorbid LB pathology did not have a notable effect on the regional FDG-PET pattern. A more DLB-like FDG-PET pattern was observed in relation to SNnl, but advanced SNnl was mostly limited to relatively pure LB cases. AD pathology may have a dominant effect over LB pathology in determining the regional neurodegeneration phenotype

A location-aware framework for intelligent real-time mobile applications

The Location-Aware Information Systems Client (LAISYC) supports intelligent, real-time, mobile applications for GPS-enabled mobile phones by dynamically adjusting platform parameters for application performance while conserving device resources such as battery life

Interstitial pneumonia with autoimmune features: a new classification still on the move.

IPAF classification criteria include several autoimmune conditions with different evolution. The progression into established CTD is common and a continuous up-to-date process of classification criteria of both IPAF and CTD is mandator

Characteristics of amnestic patients with hypometabolism patterns suggestive of Lewy body pathology

A clinical diagnosis of Alzheimer's disease dementia encompasses considerable pathological and clinical heterogeneity. While Alzheimer's disease patients typically show a characteristic temporo-parietal pattern of glucose hypometabolism on FDG-PET imaging, previous studies identified a subset of patients showing a distinct posterior-occipital hypometabolism pattern associated with Lewy body pathology. Here, we aimed to improve the understanding of the clinical relevance of these posterior-occipital FDG-PET patterns suggestive of Lewy body pathology in patients with Alzheimer's disease-like amnestic presentations. Our study included 1214 patients with clinical diagnoses of Alzheimer's disease dementia (ADD; N=305) or amnestic mild cognitive impairment (aMCI, N=909) from the Alzheimer's Disease Neuroimaging Initiative, who had FDG-PET scans available. Individual FDG-PET scans were classified as suggestive of Alzheimer's (AD-like) or Lewy body (LB-like) pathology by using a logistic regression classifier previously trained on a separate set of patients with autopsy-confirmed Alzheimer's disease or Lewy body pathology. AD- and LB-like subgroups were compared on Aβ- and tau-PET, domain-specific cognitive profiles (memory vs executive function performance), as well as the presence of hallucinations and their evolution over follow-up (≈6y for aMCI, ≈3y for ADD). 13.7% of the aMCI patients and 12.5% of the ADD patients were classified as LB-like. For both aMCI and ADD patients, the LB-like group showed significantly lower regional tau-PET burden than AD-like, but Aβ load was only significantly lower in the aMCI LB-like subgroup. LB- and AD-like subgroups did not significantly differ in global cognition (aMCI: d=0.15, p=0.16; ADD: d=0.02, p=0.90), but LB-like patients exhibited a more dysexecutive cognitive profile relative to the memory deficit (aMCI: d=0.35, p=0.01; ADD: d=0.85 p<0.001), and had a significantly higher risk of developing hallucinations over follow-up (aMCI: HR=1.8, 95% CI = [1.29, 3.04], p=0.02; ADD: HR=2.2, 95% CI = [1.53, 4.06] p=0.01). In summary, a sizeable group of clinically diagnosed ADD and aMCI patients exhibit posterior-occipital FDG-PET patterns typically associated with Lewy body pathology, and these also show less abnormal Alzheimer's disease biomarkers as well as specific clinical features typically associated with dementia with Lewy bodies

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved under- standing of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, inter- rogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain tran- scriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/