MobiRing: A Finger-Worn Wireless Motion Tracker
MobiRing: A Finger-Worn Wireless Motion Tracker
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MobiRing：手指佩戴的无线运动跟踪器
DOI：
10.1109/ithings.2014.58
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
P. Chou
中科院分区：
文献类型：
--
作者：
Yi;Yi;Kailing Huang;P. Chou
Ring是一个小巧的、可戴在手指上的无线运动跟踪平台，可以对它进行重新编程，使其具有多种功能，从而增强移动的计算能力。首先，它可以作为一个无线鼠标在空中工作，而不需要鼠标或轨迹板的表面，使其适用于增强现实或虚拟现实系统。其次，它支持收集空中笔划数据，这些数据可以被解释为命令、文本输入或原始笔划的手势。一个先进的版本可以结合联合收割机输入从额外的单位多个手指为更丰富的可能性。第三，在多个主机计算系统之间快速切换配对的能力使得Ring能够支持跨诸如PC、智能电话、平板电脑、显示墙以及甚至显示较少的嵌入式系统的拖放式操作，其中有线连接可能是不方便的，如果不是不可行的话。Ring的原型是一个超紧凑的无线传感平台，带有一个板载三轴加速度计和一个短距离无线收发器，带有一个可选的第二个加速度计，以提高精度。原型已被评估的准确性和定性的可用性，要求十名志愿新手用户尝试各种建议的操作。实验结果表明，Mobi Ring系统对鼠标类功能的识别具有直观性，对每个手势的识别准确率均在90%以上。
MobiRing is a compact, finger-worn wireless motion-tracking platform that can be reprogrammed for a wide variety of features to augmented mobile computing. First, it works as a wireless mouse in the air without requiring a surface for a mouse or a track pad, making it suitable for augmented-reality or virtual-reality systems. Second, it supports collection of stroke-in-the-air data that can be interpreted as gestures for commands, text input, or raw strokes. An advanced version can combine input from additional units on multiple fingers for richer possibilities. Third, the ability to quickly switch pairing among multiple host computing systems enables MobiRing to support drag-and-drop-like operations across systems such as PCs, smart phones, tablets, display walls, and even display less embedded systems, where a wired connection may be inconvenient if not infeasible. MobiRing has been prototyped with an ultra-compact wireless sensing platform with an on-board triaxial accelerometer and a short range wireless transceiver with an optional second accelerometer for enhanced accuracy. The prototype has been evaluated quantitatively for accuracy and qualitatively for usability by asking ten volunteer novice users to try a variety of the proposed operations. The results show that the Mobi Ring system to be intuitive for mouse-like functions and the recognition accuracy of each gesture is over 90%.