幅度符号分析:一种用于评估自主功能的工具,与传统的符号方法相补充
Alberto Porta1, Beatrice Cairo2, Vlasta Bari1
1Department of Biomedical Sciences for Health, University of Milan, Milan, Italy; Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy.
Computers in biology and medicine
|January 17, 2026
概括
幅度符号分析 (ASA) 量化了心脏周期的变化,提供了一种评估心脏控制的新方法. 这种方法补充了传统的符号分析 (SA),以全面了解心率波动.
科学领域:
- 心脏病学 心脏病学
- 生理学 生理学 生理学
- 生物医学工程 生物医学工程
背景情况:
- 符号分析 (SA) 从心脏周期 (HP) 序列估计心脏控制,但不量化HP变化率分数.
- 需要考虑绝对HP变化的方法,以更好地了解心脏自主调节.
研究的目的:
- 引入幅度符号分析 (ASA) 用于量化与符号模式类相关的HP变化.
- 评估ASA在健康个体和帕金森病患者心脏控制的特征方面的实用性.
主要方法:
- 开发了ASA,使用HP的6-bin定量化,延迟嵌入长度-3模式,并将其分类为四个模式家族.
- 应用ASA到HP数据来自健康受试者在药理和姿势挑战下,以及来自帕金森病患者和对照组.
- 计算全球和本地ASA标记,并将它们与传统的SA指数进行比较.
主要成果:
- ASA提供了一种一般方法来按符号模式类分解HP变异,以帮助评估心脏控制.
- ASA指数是SA标记物的补充,并突出了绝对HP变化和管控制之间的联系.
- 全球和本地ASA方法都产生了类似的结果,表明了稳健性.
结论:
- ASA提供了一种新的,补充SA的方法,用于详细描述心脏控制的特征.
- 同时使用SA和ASA可以更深入地了解自发心脏周期波动.
- ASA对于分析心脏自主调节,特别是其阴道组成部分是有价值的.
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