The sitting position has become one of the most common postures in developed countries. However, assuming a poor sitting posture leads to several health problems, namely back, shoulder and neck pain. In a previous work, an intelligent chair was developed and was shown to classify and correct the seating position. This work describes improvements on this intelligent chair prototype culminating with the development of a new prototype. The improvements of this new prototype are presented, resulting in new studies for posture identification. Pressure maps for 12 sitting postures were gathered in order to automatically detect user's posture through a neural network algorithm, obtaining an overall posture classification of around 81%.
Resumo: Quando Portugal começou a construir caminhos de ferro em meados da década de 1850 não existia nenhuma lei que servisse de enquadramento geral à nova atividade económica. O texto que se segue analisa de que modo a produção legislativa acompanhou o novo sector de atividade e até que ponto foi respeitada e importante no desenvolvimento da política ferroviária nacional. Para tal recorri às compilações de legislação (ferroviária e geral) disponíveis aos investigadores, comparando-as com o que se passava além-fronteiras, nomeadamente em Espanha, França e Bélgica, países que normalmente serviam de modelo à política ferroviária nacional. Palavras-chave: caminhos de ferro, legislação, Regeneração, Fontismo Abstract: When Portugal began building railroads, no general railway law was decreed. This paper describes the way the legislator met the demand for laws regulating the building and operation of railways. Then I determine to what extent this legal framework was respected and how important was it to the national railway agenda. To do so, I used the legislation compilations (of railways and otherwise) available to the researchers. Simultaneously, I kept in mind what was being done in Spain, France and Belgium, countries with which Portugal was usually compared to.Résumé: Lorsque le Portugal a commencé à construire les chemins de fer au milieu de la décennie de 1850, il ne possède aucune loi générale qui servait à l'encadrement de la nouvelle activité économique. Le texte qui suit analyse précisément de quel manière législative a accompagné le nouveau secteur d'activité et jusqu'à quel point a été respecté et a été important pour le développement de la politique ferroviaire national. Pour cela ont à recours surtout aux compilations des législations (ferroviaire et général) disponible aux investigateurs. Au même temps, je fait aussi quelques comparassions avec ce qui se passait de l'autre côté des frontières, plus précisément en Espagne, France et Belgique. Mots-clés: chemins de fer, législation, Regeneração, Fontismo.Resumen: Cuando Portugal comenzó a construir ferrocarriles, no se decretó ninguna ley ferroviaria general. Este artículo tiene como objetivo describir la forma en que el legislador cumplió con la demanda de leyes que regulan la construcción y operación de ferrocarriles. Luego determinaré en qué medida se respetó este marco legal y cuán importante fue para la agenda ferroviaria nacional. Para hacerlo, utilicé las compilaciones de legislación (de ferrocarriles y de otro tipo) disponibles para los investigadores. Simultáneamente, tuve en cuenta lo que se estaba haciendo en España, Francia y Bélgica, países con los que se suele comparar a Portugal. Palavras-llave: ferrocarriles, legislación, Regeneração, Fontismo.
In a precursory work, an intelligent sensing chair prototype was developed to classify 12 standardized sitting postures using 8 pneumatic bladders (4 in the chair's seat and 4 in the backrest) connected to piezoelectric sensors to measure inner pressure. A Classification of around 80% was obtained using Neural Networks. This work aims to demonstrate how algorithmic optimization can be applied to a newly developed prototype to improve posture classification performance. The aforementioned optimization is based on the split of users by sex and use two different previously trained Neural Networks (one for Male and the other for Female). Results showed that the best neural network parameters had an overall classification 89.0% (from the 92.1% for Female Classification and 85.8% for Male, which translates into an overall optimization of around 8%). Automatic separation of these sets was achieved with Decision Trees with an overall classification optimization of 87.1%.
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