Energy-efficient, low-latency, and non-contact eye blink detection with capacitive sensing

IF 2.4 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Mengxi Liu, Sizhen Bian, Zimin Zhao, Bo Zhou, P. Lukowicz
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引用次数: 0

Abstract

This work described a novel non-contact, wearable, real-time eye blink detection solution based on capacitive sensing technology. A custom-built prototype employing low-cost and low-power consumption capacitive sensors was integrated into standard glasses, with a copper tape electrode affixed to the frame. The blink of an eye induces a variation in capacitance between the electrode and the eyelid, thereby generating a distinctive capacitance-related signal. By analyzing this signal, eye blink activity can be accurately identified. The effectiveness and reliability of the proposed solution were evaluated through five distinct scenarios involving eight participants. Utilizing a user-dependent detection method with a customized predefined threshold value, an average precision of 92% and a recall of 94% were achieved. Furthermore, an efficient user-independent model based on the two-bit precision decision tree was further applied, yielding an average precision of 80% and an average recall of 81%. These results demonstrate the potential of the proposed technology for real-world applications requiring precise and unobtrusive eye blink detection.
通过电容式感应进行高能效、低延迟和非接触式眨眼检测
这项工作描述了一种基于电容传感技术的新型非接触、可穿戴、实时眨眼检测解决方案。采用低成本、低功耗电容式传感器的定制原型被集成到标准眼镜中,镜框上贴有铜带电极。眼睛眨动会引起电极和眼睑之间电容的变化,从而产生与电容相关的独特信号。通过分析该信号,可准确识别眨眼活动。我们通过五种不同的场景对所提出解决方案的有效性和可靠性进行了评估,共有八名参与者参与。利用用户依赖检测方法和自定义的预定义阈值,平均精确度达到 92%,召回率达到 94%。此外,还进一步应用了基于两位精度决策树的高效用户独立模型,平均精度为 80%,平均召回率为 81%。这些结果表明,所提出的技术在需要精确、无干扰的眨眼检测的实际应用中具有很大的潜力。
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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来源期刊
Frontiers in Computer Science
Frontiers in Computer Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.30
自引率
0.00%
发文量
152
审稿时长
13 weeks
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