在织心电图中对QRS检测和RRI编辑的 benchmarking 开源算法进行比较
概括
织物心电图T恤可以使用QRS探测器监测心率变化. 像xqrs这样的顶级算法即使增加了噪音和主题活动,也保持了高精度.
科学领域:
- 生物医学工程 生物医学工程
- 心血管监测 心血管监测
- 可穿戴技术可穿戴技术
背景情况:
- 在T恤衫中的织电心电图 (ECG) 传感器为医院后护理监测提供了潜力.
- 心率变化 (HRV) 分析对于临床参数至关重要,它依赖于准确检测心跳 (QRS复合体) 和它们的间隔 (RR间隔 - RRI).
- 在织ECG中缺乏QRS探测器和RRI编辑算法的全面基准测试,这阻碍了临床应用.
研究的目的:
- 使用织品心电图数据评估开源QRS探测器的性能.
- 评估这些探测器对噪音和受试者活动的稳定性.
- 在检测到的心跳上测试RRI编辑算法的有效性.
主要方法:
- 在公共数据集上评估了12个开源QRS探测器,来自13名穿T恤的健康志愿者.
- 使用MIT-BIH噪声应力测试数据库引入了额外的噪声.
- 将最先进的RRI编辑方法应用于表现最好的QRS探测器的输出.
主要成果:
- xqrs,kalidas2017和Rodrigues2021算法在杂的织品心电图数据上显示出卓越的性能 (灵敏度/精度).
- 检测器的性能基本上不受额外的噪音或不同主题活动的影响.
- 其他QRS探测器的灵敏度和/或精度不足以进行可靠的织品心电图分析.
- 当应用到xqrs结果时,RRI编辑方法在25%的受试者中成功拒绝了假阳性检测.
结论:
- 特定的QRS探测器 (xqrs,kalidas2017,Rodrigues2021) 适用于使用织品心电图进行HRV分析.
- 这些探测器在可穿戴式监控中表现出了对常见挑战的弹性,包括噪音和运动.
- RRI编辑可以进一步提高从织品心电图数据的HRV分析的可靠性.
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