Singh Dilbag, Saini B S, Kumar Vinod, Deepak Kishore K
Instrum. & Control Eng. Dept., Dr. B. R. Ambedkar Nat. Inst. of Technol., Jalandhar, Punjab, India.
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1772-5. doi: 10.1109/IEMBS.2006.259322.
Autonomic function testing forms an integral part of physiological investigations both for human and animal research. Clinically, recent times have seen them emerging as tools in settling diagnosis in several neurological, cardiovascular, endocrinal disorders where autonomic function are compromised. The reasons for such emergence have been their simplicity, noninvasiveness, and their ability to decipher the control systems. A time-varying spectrum estimation method for analyzing heart rate variability signals dynamics is presented. As a case study, the dynamics of heart rate variability during autonomic function tests is examined using wavelets. The obtained spectrum estimates have further been decomposed into separate components and, thus, the lime variation of low and high frequency components of heart rate variability can be examined separately. Thus, the present study aims to ascertain the association between heart rate changes and HRV parameters. The wavelet based HRV analysis has been found to faithfully represent the sympathovagal balance during standard autonomic battery test.
自主神经功能测试是人体和动物研究生理学调查不可或缺的一部分。在临床上,近年来它们已成为诊断多种自主神经功能受损的神经、心血管、内分泌疾病的工具。它们出现的原因在于其简单性、非侵入性以及解读控制系统的能力。本文提出一种用于分析心率变异性信号动态的时变频谱估计方法。作为案例研究,使用小波分析自主神经功能测试期间心率变异性的动态变化。所获得的频谱估计进一步分解为单独的成分,从而可以分别检查心率变异性低频和高频成分的时间变化。因此,本研究旨在确定心率变化与心率变异性参数之间的关联。基于小波的心率变异性分析已被发现能够如实地反映标准自主神经测试期间的交感迷走神经平衡。