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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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摄影电磁镜生物识别身份验证使用1D语网络

Chae Lin Seok1, Young Do Song1, Byeong Seon An1

  • 1Department of AI & Informatics, Graduate School, Sangmyung University, Hongjimun 2-Gil 20, Jongno-Gu, Seoul 03016, Republic of Korea.

Sensors (Basel, Switzerland)
|July 11, 2023
PubMed
概括
此摘要是机器生成的。

一种新的生物识别身份验证方法使用来自手腕可穿戴设备的光电脉冲图 (PPG) 数据. 一个具有多循环平均值的单维语网络实现了在虚拟环境中连续,非侵入性识别的高准确性.

关键词:
生物识别系统是生物识别系统.深度学习是一种深度学习.标识 标识 标识 标识 标识轻量级的轻量级的轻量级的轻量级的一维的语网络.摄影复合发电图谱 (Photoplethysmogram) 是一种摄影图谱.

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科学领域:

  • 生物识别和人机交互的人机交互
  • 可穿戴技术和信号处理技术

背景情况:

  • 传统的输入设备不适合元宇宙和虚拟现实 (VR) 头戴式显示环境.
  • 对于沉浸式的数字体验,需要非侵入性的,持续的生物识别身份验证.

研究的目的:

  • 提出一种新的生物识别模型,使用来自手腕可穿戴设备的光电图 (PPG) 信号.
  • 评估多循环平均方法在降低噪声和保护PPG信号特征方面的有效性.
  • 为了验证生物识别身份验证的单维语网络的性能.

主要方法:

  • 为生物识别开发了一个单维的语网络模型.
  • 在PPG信号预处理中采用了多循环平均技术,避免了传统的过器.
  • 平均周期的数量是不同的,以优化降噪和数据保真.
  • 真正和假冒的PPG数据被用于性能评估.

主要成果:

  • 多循环平均方法有效地减少了噪音,同时保留了独特的个人特征.
  • 一维的语网络在区分真实和假冒主题方面表现出强的表现.
  • 最佳配置涉及五个重叠周期,产生AUC分数为0.988和准确度为0.9723.
  • 拟议的方法显示高准确度,不论招募的受试者数量.

结论:

  • 拟议的基于PPG的生物识别模型为可穿戴设备提供了时间有效和安全的身份验证.
  • 多循环平均是PPG信号增强中传统过的可行替代方案.
  • 一维的语网络为VR/metaverse应用中持续的,非侵入性的生物识别身份验证提供了强大的框架.