Abstract
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.
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