Variations of heart rate (HR), as a normal physiological phenomenon, reflect the activities of the cardiac control system. Various components of heart rate variability (HRV) can be identified by spectral analysis. They are related to different cardiac control activities such as blood pressure, thermal regulation and respiration. Sympathetic and parasympathetic origins have been identified for specific spectral components. Analysis of HRV can provide information on automatic functions, especially the parasympathetic control by the heart. HRV has also been used to index central nervous system cholinergic functioning reflecting cognitive processes such as attention. Major clinical applications are the assessment of autonomic neuropathy in diabetics and fetal monitoring. HR is a discrete signal which is not defined between heart beats, and its single values are separated by irregular intervals. Analysis of HRV often requires its representation by a continuous function which produces data that can be regularly sampled. The description of HR in terms of instantaneous frequency of an integral pulse frequency modulator leads to new methods to obtain suitable continuous representations of HR. Spectral analysis of HRV reveals characteristic patterns; however, overlapping of components reflecting different physiological processes prevents simple decomposition. Assessment of specific cardiovascular regulatory mechanisms requires models representing their influence on heart rate and the acquisition of characteristic reference signals. Thus, decomposition of HRV by adaptive filtering has been developed to reveal numerous cardiovascular parameters such as respiratory sinus arrhythmia (RSA) and estimates of cardiac vagal tone. Quantitative determination of the various HRV components is limited by the decomposition techniques used. For the commonly applied spectral analysis of HRV, an estimate of cardiac vagal input has been defined as the variance of those HRV components correlated with respiration, an index based on mean values at the expense of information on dynamic changes. However, a continuous measure for RSA is given by the radius vector of the complex representation of RSA obtained by a Hilbert transform, which permits continuous assessment of automatic cardiovascular regulation. Both human and animal experiments support the validity and diagnostic potential of the described analysis of HRV.
|Original language||English (US)|
|Number of pages||12|
|Journal||Biomedical Engineering - Applications, Basis and Communications|
|State||Published - Jan 1 1993|
ASJC Scopus subject areas
- Biomedical Engineering