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	Provedor de dados BJMBR (2) Autor Popovic,M.B. (2) Djuric-Jovicic,M. (1) Kostic,V. (1) Mijovic,B. (1) Petrovic,I. (1) Popovic,D.B. (1) Radovanovic,S. (1) Mais... Palavra-chave Accelerometers (1) Artificial neural network (1) Control (1) Freezing of gait (1) Functional electrical stimulation (1) Neural prosthesis (1) Parkinson's disease (1) Pearson's correlation coefficient (1) Synergy (1) Time analysis (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2010 (1) 2008 (1) País Brazil (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última A simple method to assess freezing of gait in Parkinson's disease patients BJMBR Popovic,M.B.; Djuric-Jovicic,M.; Radovanovic,S.; Petrovic,I.; Kostic,V.. Freezing of gait (FOG) can be assessed by clinical and instrumental methods. Clinical examination has the advantage of being available to most clinicians; however, it requires experience and may not reveal FOG even for cases confirmed by the medical history. Instrumental methods have an advantage in that they may be used for ambulatory monitoring. The aim of the present study was to describe and evaluate a new instrumental method based on a force sensitive resistor and Pearson's correlation coefficient (Pcc) for the assessment of FOG. Nine patients with Parkinson's disease in the "on" state walked through a corridor, passed through a doorway and made a U-turn. We analyzed 24 FOG episodes by computing the Pcc between one "regular/normal" step and the rest... Tipo: Info:eu-repo/semantics/article Palavras-chave: Parkinson's disease; Freezing of gait; Time analysis; Pearson's correlation coefficient. Ano: 2010 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2010000900011 Synergistic control of forearm based on accelerometer data and artificial neural networks BJMBR Mijovic,B.; Popovic,M.B.; Popovic,D.B.. In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941). For all other movements, prediction was low (range, 0.0316-0.8302). Results suggest that the proposed algorithm is successful in generalization over... Tipo: Info:eu-repo/semantics/article Palavras-chave: Synergy; Accelerometers; Artificial neural network; Control; Neural prosthesis; Functional electrical stimulation. Ano: 2008 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2008000500007 Registros recuperados: 2 Primeira ... 1 ... Última

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