Abstract. The Speech and Language Therapy (SLT) is an area focused on the rehabilitation of people suffering from different kinds of disorders and disabilities related with language and communication. According to latest estimates of the World Health Organization, most countries do not have appropriate structures to provide healthcare and rehabilitation services for those people. This problem becomes more complex on developing countries, due the lack of professionals and ICT-based tools to support the several activities that must be performed by the Speech and Language Pathologists (SLPs). On those grounds, this paper presents a robotic assistant with the aim to help SLPs during the therapy activities. This approach is based on an integrative environment that relies on mobile ICT tools, an expert system, a knowledge layer and standardized vocabularies. This proposal has been tested on 26 children suffering from different kind of disabilities, and the results achieved have shown important improvements in some activities related with SLT like reduction of the time required to prepare patients for therapy, and better response of children to perform tasks.
Some emergent research works have identified that Agile methodologies and sustainability goals are, somehow, aligned. This alignment can be advantageously used to implement new transformation approaches with the objective of implementing a more effective adoption of both Agile and sustainably goals in organizations. Studies claim that Agile and sustainability can be geared with team collaboration and learning. Collective Intelligence has proven to be a very powerful tool, to generate solutions to complex problems, because it is able to combine the diversity of knowledge and skills of different actors into better solutions or processes, which can be extended to wider contexts. In addition, individuals participating in any collaborative process, benefit at the level of skills and new knowledge. In this article, the application of the concepts of collective intelligence to support a transformation process in which the combined adoption of the Agile and Sustainability goals is described.
Nowadays, the mobile devices (smartphones and tablets) are developed with important improvements in processing and memory capacity as well as camera resolution, massive storage or wireless connectivity. On those grounds, in developing countries these devices constitute an important alternative to develop assistive technologies to provide support in several areas as education, health care, and the elderly. Given that, in this paper we propose a new approach to handle the gesture recognition in robotic assistants that use a mobile device as main processor. In order to perform the recognition our approach uses a robust descriptor based on polygonal approximation, convex hull techniques, and the first seven HU moments. The results show 93% precision in real scenarios with different light conditions.
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