不可触及和可取消的生物识别:使用基于雷达的心脏信号在各种生理状态下识别人类
概括
这项研究引入了使用雷达获取心脏信号的可取消生物识别技术,用于安全的医疗保健识别. 这种新的方法实现了高精度,提高了生物识别数据传输的隐私.
科学领域:
- 生物识别信息 生物识别信息
- 信号处理 信号处理
- 医疗保健安全 医疗保健安全
背景情况:
- 医疗保健中的生物识别数据在网络传输过程中面临隐私和安全风险.
- 可穿戴设备,智能手机和物联网增加了数据漏洞.
- 可取消生物识别为安全,保护隐私的身份识别提供了解决方案.
研究的目的:
- 提出使用无接触心脏信号的可取消识别模型.
- 评估模型的准确性和隐私保护能力.
- 为了提高性能,比较不同的特征提取策略.
主要方法:
- 使用连续波雷达获取无接触的心脏信号.
- 用卷积神经网络 (CNN) 将信号转化为刻度图和特征提取.
- 通过高斯随机投影 (GRP) 创建可取消模板,并使用多层感知器 (MLP) 进行分类.
主要成果:
- 在所有场景中实现了91.20%的准确性,在静止场景中增加到95.40%.
- 仅在数据集上训练的CNN在特征提取方面表现优于转移学习模型.
- 证明了拟议的可取消生物识别系统的可行性.
结论:
- 拟议的可取消生物识别系统有效地保护心脏信号数据.
- 无接触式基于雷达的心脏信号与CNN相结合,提供了一个强大的识别方法.
- 该系统增强了医疗保健生物识别应用中的隐私和安全性.
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