量化从消费级光电心电学手腕带获得的间节拍间隔的精度,使用基于电心图的信息相似性方法
Xingran Cui1,2, Jing Wang1, Shan Xue1
1School of Biological Science and Medical Engineering, Southeast University, Nanjing, People's Republic of China.
消费者腕带可以在删除低信号噪声比 (SNR) 数据后准确监测心率变化 (HRV). 这改善了HRV和精神状态分类,使PPG设备在健康跟踪方面更加可靠.
科学领域:
- 生理学 生理学 生理学
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 消费级光电脉冲扫描 (PPG) 腕带提供可访问的间节拍间隔 (IBI) 和心率变化 (HRV) 数据.
- 现有的PPG衍生HRV的精度限制阻碍了其在生理学和心理生理学研究中的应用.
- 需要基于PPG的IBI准确性的定量验证方法.
研究的目的:
- 量化验证消费者PPG腕带IBI数据的准确性.
- 评估信号与噪声比 (SNR) 对HRV和精神状态分类准确性的影响.
- 为IBI准确性评估提出基于信息的相似性 (IBS) 方法.
主要方法:
- 30名健康的参与者戴着两条PPG腕带 (E4,Honor 5) 和一台黄金标准的心电图 (ECG) 装置.
- 在休息,深呼吸 (0.17 Hz, 0.1 Hz) 和精神压力条件下收集数据.
- 使用IBS方法量化PPG衍生和ECG衍生IBI时间序列之间的模式相似性,计算SNR.
主要成果:
- 最初的HRV和精神状态分类准确性是不令人满意的,因为手腕带IBI的SNR很低.
- 拒绝SNR<25的数据段显著改善了HRV的皮尔森相关系数:E4 (0.542到0.922) 和荣耀5 (0.596到0.859).
- 四类精神状态分类的平均准确性增加:E4 (77.3%至81.9%) 和荣誉5 (79.3%至83.3%).
结论:
- 在删除低SNR段之后,消费级PPG腕带可用于HR和HRV监控.
- 拟议的IBS方法有效量化了非心电图系统的IBI和HRV精度.
- 数据质量过对于可穿戴PPG设备的可靠生理见解至关重要.
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