Accessible Interface for Context Awareness in Mobile Devices for Users With Memory Impairment

Iyad Abu Doush, Sanaa Jarrah
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引用次数: 4

Abstract

Memory problems usually appear because of aging or may happen because of a brain injury. Such problems prevent the person from performing daily activities. In this paper, the authors propose a framework to develop a smartphone solution to detect and recognize the user context. In order to build the context detection framework, the authors compare three different machine learning techniques (C.4.5, random, and BFTree) in terms of context detection accuracy. Then, the authors use the classification technique with the highest accuracy in a mobile application to help users by detecting their context. The authors develop two interfaces based on the suggested accessibility features for users with memory impairment. Two scenarios are used to evaluate the user interface, and the results prove the applicability and the usability of the proposed context detection framework.
为记忆障碍用户在移动设备中提供上下文感知的可访问接口
记忆问题通常是由于衰老或脑损伤而出现的。这些问题使患者无法进行日常活动。在本文中,作者提出了一个框架来开发智能手机解决方案,以检测和识别用户上下文。为了构建上下文检测框架,作者在上下文检测准确性方面比较了三种不同的机器学习技术(C.4.5, random和BFTree)。然后,作者在移动应用程序中使用最高准确率的分类技术来帮助用户检测他们的上下文。作者根据建议的可访问性特性为有记忆障碍的用户开发了两个界面。用两个场景对用户界面进行了评估,结果证明了所提出的上下文检测框架的适用性和可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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