Advancing Hand Gesture Recognition with High Resolution Electrical Impedance Tomography

被引：95
|
作者：
Zhang, Yang [1 ]
Xiao, Robert [1 ]
Harrison, Chris [1 ]
机构：
[1] Carnegie Mellon Univ, Human Comp Interact Inst, 5000 Forbes Ave, Pittsburgh, PA 15213 USA
来源：
UIST 2016: PROCEEDINGS OF THE 29TH ANNUAL SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY | 2016年
关键词：
Electrical Impedance Tomography; EIT; hand gestures; smartwatch; bio-impedance; biometrics; input; SYSTEM; BRAIN;
D O I：
10.1145/2984511.2984574
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Electrical Impedance Tomography (EIT) was recently employed in the HCI domain to detect hand gestures using an instrumented smartwatch. This prior work demonstrated great promise for non-invasive, high accuracy recognition of gestures for interactive control. We introduce a new system that offers improved sampling speed and resolution. In turn, this enables superior interior reconstruction and gesture recognition. More importantly, we use our new system as a vehicle for experimentation - we compare two EIT sensing methods and three different electrode resolutions. Results from in-depth empirical evaluations and a user study shed light on the future feasibility of EIT for sensing human input.
引用
收藏
页码：843 / 850
页数：8
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