智能手机惯性单位估计的瞬间呼吸和心率的准确性
Eliana Cinotti1, Jessica Centracchio1, Salvatore Parlato1
1Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, I-80125 Naples, Italy.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
智能手机的惯性传感器通过地震心电图 (SCG) 和心肌图 (GCG) 准确地测量心脏和呼吸率. 这使得无需额外设备的非侵入性心肺呼吸系统监测成为可能.
科学领域:
- 生物医学工程 生物医学工程
- 心脏呼吸系统监测 监测心脏呼吸系统
- 可穿戴技术可穿戴技术
背景情况:
- 地震心脏图 (SCG) 和心筋梗塞图 (GCG) 使用胸壁加速和角速度.
- 呼吸会导致信号干扰,但智能手机集成提供了潜在的可能性.
- 准确的心肺呼吸系统监测对于健康评估至关重要.
研究的目的:
- 评估智能手机惯性传感器的准确性,以同时测量心率和呼吸率.
- 评估SCG和GCG在检测心跳和呼吸过程中的性能.
- 使用智能手机传感器验证心跳间隔 (IBI) 和呼吸间隔 (IBrI) 间隔估计.
主要方法:
- 从使用智能手机休息的10名健康受试者获得SCG和GCG信号.
- 用智能手机获得的SCG/GCG数据与心电图和呼吸带信号进行比较.
- 分析了心跳和呼吸行为检测准确度,灵敏度和正预测值 (PPV).
- 通过布兰德-阿尔特曼分析和R平方值评估的节拍间隔和呼吸间隔估计.
主要成果:
- 对于心跳检测,GCG表现出高灵敏度 (97.3%) 和PPV (97.9%).
- SCG和GCG显示出高精度的呼吸行为检测 (灵敏度>95%,PPV>92%).
- IBI和IBrI的估计显示出强烈的线性关系 (R2 > 0.999和R2 > 0.968),偏差最小,共识极限窄.
结论:
- 智能手机的惯性传感器可以准确地测量瞬间的心脏和呼吸率.
- 当SCG和GCG来自智能手机时,它们提供了一个可行的非侵入性心肺呼吸系统监测解决方案.
- 这项技术消除了对额外专用监控设备的需求.
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