Eyelid Gestures on Mobile Devices for People with Motor Impairments

Mingming Fan, Zhuguo Li, Franklin Mingzhe Li
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引用次数: 18

Abstract

Eye-based interactions for people with motor impairments have often used clunky or specialized equipment (e.g., eye-trackers with non-mobile computers) and primarily focused on gaze and blinks. However, two eyelids can open and close for different duration in different orders to form various eyelid gestures. We take a first step to design, detect, and evaluate a set of eyelid gestures for people with motor impairments on mobile devices. We present an algorithm to detect nine eyelid gestures on smartphones in real-time and evaluate it with twelve able-bodied people and four people with severe motor impairments in two studies. The results of the study with people with motor-impairments show that the algorithm can detect the gestures with .76 and .69 overall accuracy in user-dependent and user-independent evaluations. Moreover, we design and evaluate a gesture mapping scheme allowing for navigating mobile applications only using eyelid gestures. Finally, we present recommendations for designing and using eyelid gestures for people with motor impairments.
运动障碍人士在移动设备上的眼睑手势
运动障碍患者的基于眼睛的互动通常使用笨重或专门的设备(例如,带有非移动电脑的眼球追踪器),主要集中在凝视和眨眼上。然而,两眼眼睑可以按不同的顺序开合不同的时间,形成不同的眼睑手势。我们迈出了第一步,为移动设备上的运动障碍人士设计、检测和评估一套眼睑手势。我们提出了一种算法,可以实时检测智能手机上的九种眼睑手势,并在两项研究中对12名健全的人和4名严重运动障碍的人进行了评估。对运动障碍患者的研究结果表明,该算法在用户依赖和用户独立评估中检测手势的总体准确率分别为0.76和0.69。此外,我们设计并评估了一个手势映射方案,允许仅使用眼睑手势导航移动应用程序。最后,我们提出建议,设计和使用眼睑手势的人有运动障碍。
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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