Budrionis Andrius, Plikynas Darius, Daniušis Povilas, Indrulionis Audrius
Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Vilnius, Lithuania.
Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway.
Assist Technol. 2022 Mar 4;34(2):178-194. doi: 10.1080/10400435.2020.1743381. Epub 2020 Apr 17.
Given the growth in the numbers of visually impaired (VI) people in low-income countries, the development of affordable electronic travel aid (ETA) systems employing devices, sensors, and apps embedded in ordinary smartphones becomes a potentially cost-effective and reasonable all-in-one solution of utmost importance for the VI. This paper offers an overview of recent ETA research prototypes that employ smartphones for assisted orientation and navigation in indoor and outdoor spaces by providing additional information about the surrounding objects. Scientific achievements in the field were systematically reviewed using PRISMA methodology. Comparative meta-analysis showed how various smartphone-based ETA prototypes could assist with better orientation, navigation, and wayfinding in indoor and outdoor environments. The analysis found limited interest among researchers in combining haptic interfaces and computer vision capabilities in smartphone-based ETAs for the blind, few attempts to employ novel state-of-the-art computer vision methods based on deep neural networks, and no evaluations of existing off-the-shelf navigation solutions. These results were contrasted with findings from a survey of blind expert users on their problems in navigating in indoor and outdoor environments. This revealed a major mismatch between user needs and academic development in the field.
鉴于低收入国家视障人士数量的增长，开发经济实惠的电子出行辅助（ETA）系统成为一项极具成本效益且合理的一体化解决方案，对视障人士至关重要，该系统采用普通智能手机中嵌入的设备、传感器和应用程序。本文概述了近期的ETA研究原型，这些原型通过提供有关周围物体的额外信息，利用智能手机在室内和室外空间进行辅助定向和导航。使用PRISMA方法对该领域的科学成果进行了系统综述。比较荟萃分析表明，各种基于智能手机的ETA原型如何在室内和室外环境中协助更好地定向、导航和寻路。分析发现，研究人员对将触觉界面和计算机视觉功能结合在基于智能手机的盲人ETA中的兴趣有限，很少有人尝试采用基于深度神经网络的新颖的最新计算机视觉方法，并且没有对现有的现成导航解决方案进行评估。这些结果与对视障专家用户在室内和室外环境中导航问题的调查结果形成对比。这揭示了用户需求与该领域学术发展之间的重大不匹配。
