网络安全端到端FPGA加速ECG监控,用于通过个性化CWT和对抗防御进行精确诊断
IEEE journal of biomedical and health informatics
|December 8, 2025
概括
本研究介绍了一种安全的实时边缘可穿戴的心电图监测系统,使用个性化的连续波段转换 (CWT) 和对抗防御来增强心血管诊断.
科学领域:
- 生物医学工程 生物医学工程
- 网络安全 网络安全
- 边缘计算 边缘计算
背景情况:
- 可穿戴技术和边缘计算正在改变心血管监测.
- 越来越需要私有,安全和实时诊断解决方案.
- 现有系统在平衡准确性,隐私和资源限制方面面临挑战.
研究的目的:
- 提出一个边缘可穿戴的ECG监控系统,增强隐私和安全性.
- 在资源有限的硬件上实现高诊断精度和实时推断.
- 为了减轻隐私风险并提高对抗攻击的稳定性.
主要方法:
- 集成个性化的连续波形变换 (CWT) 功能提取和隐私保护.
- 实施一个DeepFool-FGSM对抗防御策略与量子化意识训练 (QAT).
- 在现场可编程网关数组 (FPGA) 上部署了优化的并行PoolFormer架构.
主要成果:
- 在FPGA上实现了98.93%的高诊断准确度.
- 证明了实时推断,延迟低于1.7毫秒.
- 在低FPGA核心功耗 (0.055W) 的情况下,表现出对抗对抗干扰的强度提高.
结论:
- 开发的系统提供了一个网络安全,个性化的ECG监测解决方案.
- 它确保了心血管诊断的保密性,完整性和可用性.
- 该系统有效地平衡了可穿戴应用程序的性能,安全性和资源效率.
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