Novel approaches to long-term heart rate variability, including non-Gaussianity index and heart rate turbulence, provide useful autonomic function indicators beyond classical LF and HF measurements.
In the assessment of autonomic function by heart rate variability (HRV), the framework that the power of high-frequency component or its surrogate indices reflects parasympathetic activity, while the power of low-frequency component or LF/HF reflects sympathetic activity has been used as the theoretical basis for the interpretation of HRV. Although this classical framework has contributed greatly to the widespread use of HRV for the assessment of autonomic function, it was obtained from studies of short-term HRV (typically 5‑10 min) under tightly controlled conditions. If it is applied to long-term HRV (typically 24 h) under free-running conditions in daily life, erroneous conclusions could be drawn. Also, long-term HRV could contain untapped useful information that is not revealed in the classical framework. In this review, we discuss the limitations of the classical framework and present studies that extracted autonomic function indicators and other useful biomedical information from long-term HRV using novel approaches beyond the classical framework. Those methods include non-Gaussianity index, HRV sleep index, heart rate turbulence, and the frequency and amplitude of cyclic variation of heart rate.
Hayano et al. (2021) conducted a review in Autonomic function assessment. Novel approaches to long-term heart rate variability vs. Classical framework of LF and HF measurements was evaluated. Novel approaches to long-term heart rate variability, including non-Gaussianity index and heart rate turbulence, provide useful autonomic function indicators beyond classical LF and HF measurements.