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COMBAHO: A deep learning system for integrating brain injury patients in society

机译:Combaho​​:一种深入学习系统,用于整合社会脑损伤患者

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In the last years, the care of dependent people, either by disease, accident, disability, or age, is one of the current priority research topics in developed countries. Moreover, such care is intended to be at patients home, in order to minimize the cost of therapies. Patients rehabilitation will be fulfilled when their integration in society is achieved, either in the family or in a work environment. To address this challenge, we propose the development and evaluation of an assistant for people with acquired brain injury or dependents. This assistant is twofold: in the patient's home is based on the design and use of an intelligent environment with abilities to monitor and active learning, combined with an autonomous social robot for interactive assistance and stimulation. On the other hand, it is complemented with an outdoor assistant, to help patients under disorientation or complex situations. This involves the integration of several existing technologies and provides solutions to a variety of technological challenges. Deep leaning-based techniques are proposed as core technology to solve these problems. (C) 2019 Elsevier B.V. All rights reserved.
机译:在过去的几年中,依赖于疾病,意外,残疾或年龄的依赖者的照顾是发达国家目前的优先研究主题之一。此外,这种护理旨在在患者家中,以最小化疗法的成本。患者康复将在其在社会的整合,无论是在家庭中还是在工作环境中都会实现。为了解决这一挑战,我们为获得脑损伤或家属的人们提出了对助理的开发和评估。这位助手是双重的:在患者的家中,基于设计和使用一个智能环境的能力来监测和主动学习,结合自主社会机器人进行互动辅助和刺激。另一方面,它与一个户外助手相辅相成,帮助患者在迷失方向或复杂的情况下。这涉及若干现有技术的整合,并为各种技术挑战提供解决方案。基于深度的基于倾斜的技术被提出为解决这些问题的核心技术。 (c)2019 Elsevier B.v.保留所有权利。

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