27,329 research outputs found
Model-based control of FES embedding simultaneous volitional EMG measurement
There are over one million people in the UK with upper limb impairment following stroke. Artificial activation of muscle can be achieved using functional electrical stimulation (FES), and enable recovery by facilitating task practice. Significant clinical research supports the utility of FES for both orthotic and therapeutic purposes, and shows that the effectiveness is maximised when applied concurrently with a patient’s voluntary effort. Voluntary effort can be captured using electromyography (EMG), however existing FES control schemes using EMG are predominantly open-loop and fail to provide accurate assistance.In this paper, a model of the dynamic interaction between voluntary and evoked muscle activation is developed, embedding both nonlinear recruitment and activation dynamics. Then an identification method is proposed suitable for clinical application. This enables a model-based, hybrid EMG/FES control scheme to be developed, allowing the dual objectives of tracking and volitional intention support to be optimized for the first time. Experimental results show that the tracking performance of the controller is far more effective compared to previous FES approaches which neglect voluntary action.</p
Iterative learning control of FES with embedded simultaneous volitional EMG
Seventeen million people are left with limb impairment following stroke, and there is an urgent need for new effective rehabilitation technology. Functional electrical stimulation (FES) has been shown to facilitate motor re-learning by artificially activating muscles during practice of motor tasks, however clinical outcomes depend on how closely FES matches the intended motion. Electromyography (EMG) signals recorded from muscle can capture voluntary intention, and have successfully been employed in openloop FES controllers. Likewise, model-based controllers using force and/or position data have yielded accurate movement control in clinical trials. Iterative learning control (ILC) in particular has been successful in clinical tests, since the process of rehabilitationis inherently iterative. This paper develops a new control strategy to combine both EMG and model-based control. It begins by developing a novel hybrid model of muscle dynamics incorporating both EMG and FES. ILC is then employed to enable precise control over both variables, thereby offering substantial improvements over existing control schemes in the domain of stroke rehabilitation. Experimental results confirm efficacy of the hybrid control scheme, as well as its suitability for clinical application
The construction of Karen Karnak: The multi-author-function
This thesis is situated within the comparatively recent developments of Web 2.0 and the emergence of interactive WikiMedia, and explores the mode of authorship within a Read/Write culture compared to that of a Read/Only tradition. The hypothesis of this study is that the role of the audience has become merged with the author, and as such, represents new functions and attributes, distinct from a more conventional concept of authorship, in which the roles of audience and author are more separate. Read/Write and participatory culture, as defined by this study, is focused on collaboration, and includes the influences of D.I.Y. culture, Open-Source practices and the production of text by multiple authors. Multi-authorship presents a re-thinking of several concepts which support the notion of the individual author, since the focus of multi-authorship is not on attribution and ownership of a finished text, but on the continued malleability of a text. Modes of multi-authorship, demonstrated in the use of the pseudonyms Alan Smithee and Karen Eliot, represent declarative authors whose names signify multiple origins, whilst concurrently indicating a distinct body of work. The function of these names form an important context to this study, since primary research involves the construction of an experimental mode of multi-authorship utilising WikiMedia technology and the interaction of thirty nine participants, who are invited to create a body of work under the collective pseudonym Karen Karnak. The data generated by this experiment is analysed using aspects of Michel Foucault's author-function to identify and determine power structures inherent in the WikiMedia context. The interplay of power structures, including concepts such as identity, ownership and the body of work, affect the resulting mode of authorship and contribute to the construction of Karen Karnak, suggesting further areas of research into the emerging multi-author
Iterative learning control of functional electrical stimulation in the presence of voluntary user effort
Worldwide 17 million people are left with impairment to their upper or lower limb following stroke. Functional electrical stimulation (FES) is a method of artificially activating muscles using electrical pulses and is the most common rehabilitation technology. A significant body of clinical research confirms that successful rehabilitation requires FES to be applied in a way that supports voluntary intention during repeated attempts at functional tasks. Electromyography (EMG) measures the voluntary contraction of muscles and has been used to directly control FES in openloop, however it is limited by poor accuracy. On the other hand, model-based feedback control can provide high accuracy, but does not explicitly promote voluntary intention.A new dynamic model of the muscle activation, generated by combined voluntary nerve signals and FES, is developed in this paper. It includes both nonlinear recruitment and linear activation dynamics. An efficient identification procedure is then formulated which can be applied to people with stroke. A model-based hybrid EMG/FES control scheme is then derived based on the model structure, allowing tracking and volitional intention support to be simultaneously optimised for the first time. Exploiting the repeated nature of rehabilitation, the control framework is then extended to further improve tracking accuracy. That is achieved by learning from experience through iterative learning control. The framework is experimentally tested with results confirming it can deliver greater performance compared to existing FES approaches, which do not consider voluntary action in the model or controller
L'effet canonique : une nouvelle perspective sur le concept objectal et sa représentation linguistique
Sinha Chris, Freeman Norman H., Schmoll Patrick. L'effet canonique : une nouvelle perspective sur le concept objectal et sa représentation linguistique. In: Bulletin de psychologie, tome 34 n°351, 1981. Groupe d'études du langage II, Université de Strasbourg. pp. 713-723
Model-based control of FES embedding simultaneous voluntary user effort
There are over 1.2 million people in the UK with upper or lower limb impairment following stroke. Artificial activation of muscle can be achieved using functional electrical stimulation (FES), which is the most prevalent assistive technology used in the rehabilitation of stroke patients. Significant clinical research shows that effective treatment requires electrical pulses to be delivered to muscles in a manner which supports voluntary effort, during performance of repetitive rehabilitation tasks. This has motivated using electromyography (EMG) to measure the voluntary contraction and then to control electrical stimulation supplied to impaired muscles. However, existing FES control schemes using EMG are predominantly open loop and fail to provide accurate assistance to achieve the intended movement. In this thesis, a model of dynamic interaction between voluntary and evoked muscle activation is initially developed, embedding both nonlinear recruitment and activation dynamics. This enables the proposed model-based, hybrid EMG/FES control scheme to be derived, allowing the dual objectives of tracking and volitional intention support to be optimised. Extension of the model-based EMG/FES structure to embed iterative learning control (ILC) is then undertaken in order to augment the tracking accuracy by learning from experience to update the control action. Experimental results show that the identification scheme is accurate and suitable for clinical application. Further results show that the model-based ILC framework using hybrid activation reduces the tracking error by between 27% and 70% compared to previous FES approaches which neglect voluntary action. Identifying a model of EMG/FES muscle activation is time-consuming and accuracy is degraded by fatigue and other time-varying properties. To address these issues, an adaptive control scheme is then developed termed ‘estimation-based multiple model ILC’ (EMMILC). This control framework automatically selects a controller based on the most appropriate model chosen from an underlying set of ‘candidate models’. A design procedure is proposed to generate a set of models based on distributions of fatigue tests. Results indicate that EMMILC framework has a significant improvement in tracking between 50% and 112% despite the changing model over time due to fatigue effect compared to standard ILC designed using a single model. Additional results confirm the potential of the proposed framework to be applied without the need of model identification
Language Change and SA-OT: The case of sentential negation
Simulated Annealing for Optimality Theory (SA-OT) updates Optimality Theory by adding a model of performance to a theory of linguistic competence. Our aim is to show that SA-OT can contribute to language change simulations. Performance "errors" are considered to be one of the causes of variation and change. We have chosen to model the evolution of sentential negation (SN). The descriptive background adopts Jespersen's Cycle, according to which the evolution of sentential negation follows three main stages (1. pre-verbal, 2. discontinuous, and 3. post-verbal). Therefore, we advance a novel model for SN, based on SA-OT. It reproduces the three pure and the two observed mixed stages, whereas it correctly predicts the lack of an intermediate stage between 3 and 1. The success of the approach corroborates the computational, performance-based approach to the data. Finally, we employ the iterated learning paradigm to reproduce historical changes in a "simulated corpus study". This enterprise turns out to be more difficult than one would naively believe.Appeared open access as: Computational Linguistics in the Netherlands Journal (CLIN), vol. 1 (2011), pp. 21-40, and is available at http://www.clinjournal.org/sites/default/files/Lopopolo.pdfA. Lopopolo and Biró, T., “Language Change and SA-OT. The case of sentential negation”, Computational Linguistics in the Netherlands Journal, vol. 1, pp. 21-40, 2011.Peer Reviewe
Mr. H. Peterman
Verso: [imprinted] A. Freeman, Artist in Photography, Dallas, Texas., All kinds of Photographing done in the latest style., Prices moderate, and satisfaction guaranteed.; [handwritten] Dear Papa, Mr. H. Peterman, 288 Sang a center, SA
Jean Dufournet, Michael Freeman et Jean Dérens (dir.), Villon et ses lecteurs
Si la bibliographie des études villoniennes est aujourd’hui florissante, les productions non scientifiques, écrits inspirés par Villon, poésie et romans modelés autour de sa vie imaginaire ou de sa production réelle, expriment la fascination du public moderne et un rayonnement incomparable à nul autre auteur de la fin du Moyen Âge. S’interroger sur les « lecteurs » de Villon depuis le XVe siècle jusqu’à nos jours, comme le proposent les organisateurs J. Dufournet, M. Freeman et J. Dérens, rev..
Jean Dufournet, Michael Freeman et Jean Dérens (dir.), Villon et ses lecteurs
Si la bibliographie des études villoniennes est aujourd’hui florissante, les productions non scientifiques, écrits inspirés par Villon, poésie et romans modelés autour de sa vie imaginaire ou de sa production réelle, expriment la fascination du public moderne et un rayonnement incomparable à nul autre auteur de la fin du Moyen Âge. S’interroger sur les « lecteurs » de Villon depuis le XVe siècle jusqu’à nos jours, comme le proposent les organisateurs J. Dufournet, M. Freeman et J. Dérens, rev..
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