从单轴地震心图进行基于自适应自相关的心率估计:跨六个不同数据集的综合基准.
IEEE journal of biomedical and health informatics
|February 18, 2026
概括
一种名为自适应自相关函数探测器 (AACFD) 的新方法,使用单个加速计轴,从地震心电图 (SCG) 中准确估计心率 (HR). 这种轻量级的自动管道在休息数据上实现了小于bpm的准确性,以及对各种心脏病的临床可接受结果.
科学领域:
- 生物医学工程 生物医学工程
- 心血管生理学心血管生理学
- 信号处理 信号处理
背景情况:
- 地震心谱 (SCG) 提供了一种非侵入性方法来监测心率 (HR).
- 现有的基于SCG的HR估计方法通常需要ECG校准或机器学习,这限制了它们的适用性.
- 需要轻量化,自动化和无校准算法来从SCG进行HR估计.
研究的目的:
- 引入和验证自适应自相对应函数检测器 (AACFD),这是一个新的管道,用于从单轴SCG进行窗口平均HR估计.
- 证明AACFD能够在没有ECG校准或机器学习的情况下运行,使其广泛可用.
- 评估AACFD在各种数据集中的表现,包括健康受试者和心血管疾病患者.
主要方法:
- AACFD结合了适应性SCG信封的YIN风格差异函数分析与3秒段的短窗口自相对应.
- 基于特征的权重策略融合了两个检测分支,结合了信号质量指数和多尺度特征.
- 汉佩尔过和时间一致性检查用于删除异常窗口,确保稳定性.
主要成果:
- 在静止数据集 (MCG,CEBS) 上,AACFD的平均绝对误差 (MAE) 低于1bpm.
- 在膜心脏病 (VHD) 和侵袭性右心导管注射 (RHC) 队列中观察到临床上可接受的MAE (分别在30s窗口上分别为4.38bpm和3.58bpm).
- 超过90%的非重叠的10-60秒窗口通过了所有数据集的质量控制,表明了高可用性.
结论:
- AACFD算法从单轴SCG提供准确的窗口平均HR估计,即使在具有挑战性的临床和移动环境中.
- 它的轻量级和自动性质允许在商品硬件上实时实现.
- AACFD代表了非侵入性心脏监测的重大进步,特别是对于ECG无法或不切实际的应用.
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