Gait Pattern Adaptation for an Active Lower-Limb Orthosis Based on Neural Networks

This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011

Synaptic compensation on Hopfield network: implications for memory rehabilitation

The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

One size doesn't fit all: Research methodologies in a language variation study of Sudanese teens

The research reported here draws on a study of five teenagers from a Dinka-speaking community of Sudanese settling in Australia. A range of factors including language proficiency, social network structure and language attitudes are examined as possible causes for the variability of language use. The results and discussion illustrate how the use of a triangular research approach captured the complexity of the participants' language situation and was critical to developing a full understanding of the interplay of factors influencing the teens' language maintenance and shift in a way that no single method could. Further, it shows that employment of different methodologies allowed for flexibility in data collection to ensure the fullest response from participants. Overall, this research suggests that for studies of non-standard communities, variability in research methods may prove more of a strength that the use of standardised instruments and approaches.

White matter microstructure underlying default mode network connectivity in the human brain

Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain The underlying structural basis of this functional connectivity pattern is still widely unexplored We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure e 7 underlying default mode connectivity We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data Would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus With lateral temporal lobes, medial temporal lobes, and precuneus This was demonstrated at the p<0001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data Out findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based oil distinct pattern of anatomical connectivity within the cerebral white matter (C) 2009 Elsevier Inc All rights reserved

Inhibitory network interactions shape the auditory processing of natural communication signals in the songbird auditory forebrain

The role of GABA in the central processing of complex auditory signals is not fully understood. We have studied the involvement of GABA(A)-mediated inhibition in the processing of birdsong, a learned vocal communication signal requiring intact hearing for its development and maintenance. We focused on caudomedial nidopallium (NCM), an area analogous to parts of the mammalian auditory cortex with selective responses to birdsong. We present evidence that GABA(A)-mediated inhibition plays a pronounced role in NCM`s auditory processing of birdsong. Using immunocytochemistry, we show that approximately half of NCM`s neurons are GABAergic. Whole cell patch-clamp recordings in a slice preparation demonstrate that, at rest, spontaneously active GABAergic synapses inhibit excitatory inputs onto NCM neurons via GABA(A) receptors. Multi-electrode electrophysiological recordings in awake birds show that local blockade of GABA(A)-mediated inhibition in NCM markedly affects the temporal pattern of song-evoked responses in NCM without modifications in frequency tuning. Surprisingly, this blockade increases the phasic and largely suppresses the tonic response component, reflecting dynamic relationships of inhibitory networks that could include disinhibition. Thus processing of learned natural communication sounds in songbirds, and possibly other vocal learners, may depend on complex interactions of inhibitory networks.

Human cortical processing of colour and pattern

The present study investigates human visual processing of simple two-colour patterns using a delayed match to sample paradigm with positron emission tomography (PET). This study is unique in that we specifically designed the visual stimuli to be the same for both pattern and colour recognition with all patterns being abstract shapes not easily verbally coded composed of two-colour combinations. We did this to explore those brain regions required for both colour and pattern processing and to separate those areas of activation required for one or the other. We found that both tasks activated similar occipital regions, the major difference being more extensive activation in pattern recognition. A right-sided network that involved the inferior parietal lobule, the head of the caudate nucleus, and the pulvinar nucleus of the thalamus was common to both paradigms. Pattern recognition also activated the left temporal pole and right lateral orbital gyrus, whereas colour recognition activated the left fusiform gyrus and several right frontal regions. (C) 2001 Wiley-Liss, Inc.

sMapReduce: a programming pattern for wireless sensor networks

Wireless Sensor Networks (WSNs) are increasingly used in various application domains like home-automation, agriculture, industries and infrastructure monitoring. As applications tend to leverage larger geographical deployments of sensor networks, the availability of an intuitive and user friendly programming abstraction becomes a crucial factor in enabling faster and more efficient development, and reprogramming of applications. We propose a programming pattern named sMapReduce, inspired by the Google MapReduce framework, for mapping application behaviors on to a sensor network and enabling complex data aggregation. The proposed pattern requires a user to create a network-level application in two functions: sMap and Reduce, in order to abstract away from the low-level details without sacrificing the control to develop complex logic. Such a two-fold division of programming logic is a natural-fit to typical sensor networking operation which makes sensing and topological modalities accessible to the user.

The evolution of user mobility on the Eduroam network

The emergence of smartphones with Wireless LAN (WiFi) network interfaces brought new challenges to application developers. The expected increase of users connectivity will impact their expectations for example on the performance of background applications. Unfortunately, the number and breadth of the studies on the new patterns of user mobility and connectivity that result from the emergence of smartphones is still insufficient to support this claim. This paper contributes with preliminary results on a large scale study of the usage pattern of about 49000 devices and 31000 users who accessed at least one access point of the eduroam WiFi network on the campuses of the Lisbon Polytechnic Institute. Results confirm that the increasing number of smartphones resulted in significant changes to the pattern of use, with impact on the amount of traffic and users connection time.

Fractional central pattern generators for bipedal locomotion

Locomotion has been a major research issue in the last few years. Many models for the locomotion rhythms of quadrupeds, hexapods, bipeds and other animals have been proposed. This study has also been extended to the control of rhythmic movements of adaptive legged robots. In this paper, we consider a fractional version of a central pattern generator (CPG) model for locomotion in bipeds. A fractional derivative D α f(x), with α non-integer, is a generalization of the concept of an integer derivative, where α=1. The integer CPG model has been proposed by Golubitsky, Stewart, Buono and Collins, and studied later by Pinto and Golubitsky. It is a network of four coupled identical oscillators which has dihedral symmetry. We study parameter regions where periodic solutions, identified with legs’ rhythms in bipeds, occur, for 0<α≤1. We find that the amplitude and the period of the periodic solutions, identified with biped rhythms, increase as α varies from near 0 to values close to unity.

Web GIS to support irrigation management: a prototype for SAGRA network, Alentejo Portugal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Social network analysis applied to knowledge creation and transfer in the portuguese agricultural R&D field: an exploratory study

Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm

Model morphisms (MoMo) to enable language independent information models and interoperable business networks

MSc. Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering

Impact of europeanization in policy network governance pattrons

Comunicação apresentada na 30th Sunbelt Social Networks Conference, em Riva del Garda, Itália, a 3 de Julho de 2010.

Sentiment analysis on twitter for the portuguese language

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.