Xavier Rita, Laranjo Sérgio, Ducla-Soares Eduardo, Andrade Alexandre, Boto J P, Santos-Bento Mariana, Ducla-Soares José Luis, Carvalho Luís Silva, Rocha Isabel
Institute of Physiology, Faculty of Medicine of Lisbon, Lisbon, Portugal.
Rev Port Cardiol. 2008 Apr;27(4):435-41.
The Valsalva maneuver is an autonomic test that evokes short sharp cardiovascular fluctuations mediated by the autonomic nervous system. Numerous spectral analysis methods have been proposed to analyze biological signals. When applied to heart rate (HR) variability, two major bands related to autonomic influence have been defined: LF (mainly sympathetic) and HF (parasympathetic). However, conventional spectral approaches are based on the assumption of stationarity, and most require at least five minutes of recording. These two requirements cannot be fulfilled when analysis of dynamic processes such as the regulatory action of the autonomic nervous system is required. Wavelet transform is a mathematical tool that, by determining the temporal localization of the changes, the frequencies involved and their contribution to the entire signal, overcomes the limitations imposed by conventional methods. In the present work, we use wavelets to evaluate autonomic influence through the LF and HF band powers on acute changes in systolic blood pressure (sBP) and RR intervals (RRI) during the Valsalva maneuver. Eighteen healthy volunteers performed the maneuver by blowing, after a deep inspiration and with a closed glottis, against a pressure of 40 mmHg for 15 seconds. Data were analyzed in three different periods: 1) the last minute just prior to the test (CTR); 2) the 15 seconds of the Valsalva maneuver (VM); 3) during the next 35 seconds after the maneuver (aVM). We observed that LF power increased in sBP and RRI in both VM and ower only increased after Valsalva. The data showed a marked increase in sympathetic activity during and after the maneuver and an increase in parasympathetic outflow after aVM. In conclusion, the ability of wavelets to analyze short non-stationary signals makes wavelet transform a promising tool to evaluate physiological and pathological autonomic conditions.
瓦尔萨尔瓦动作是一种自主神经测试,可引发由自主神经系统介导的短暂剧烈心血管波动。已经提出了许多频谱分析方法来分析生物信号。当应用于心率(HR)变异性时,已定义了与自主神经影响相关的两个主要频段:低频(主要是交感神经)和高频(副交感神经)。然而,传统的频谱方法基于平稳性假设,并且大多数方法至少需要五分钟的记录。当需要分析诸如自主神经系统的调节作用等动态过程时,这两个要求无法满足。小波变换是一种数学工具,通过确定变化的时间定位、所涉及的频率及其对整个信号的贡献,克服了传统方法所带来的局限性。在本研究中,我们使用小波通过低频和高频频段功率来评估自主神经对瓦尔萨尔瓦动作期间收缩压(sBP)和RR间期(RRI)急性变化的影响。18名健康志愿者在深吸气后屏气,以40 mmHg的压力吹气15秒来进行该动作。数据在三个不同时期进行分析:1)测试前的最后一分钟(CTR);2)瓦尔萨尔瓦动作的15秒(VM);3)动作后的接下来35秒(aVM)。我们观察到,在VM和aVM期间,sBP和RRI中的低频功率均增加,而高频功率仅在瓦尔萨尔瓦动作后增加。数据显示,动作期间和之后交感神经活动显著增加,而在aVM后副交感神经流出增加。总之,小波分析短时间非平稳信号的能力使小波变换成为评估生理和病理自主神经状况的有前途的工具。