Frequency domain analysis of heart rate variability (HRV) is a noninvasive method to evaluate the autonomic nervous system (ANS), but the traditional parameters of HRV, i.e., the power spectra of the high-frequency (HF) and low-frequency bands (LF), cannot estimate the activity of the parasympathetic (PNS) and sympathetic nervous systems (SNS) well. The aim of our study was to provide a corrected method to better distinguish the contributions of the PNS and SNS in the HRV spectrum. Respiration has a gating effect on cardiac vagal efferent activity, which induces respiration-locked heart rate (HR) changes because of the fast effect of the PNS. So the respiration-related heart rate (HR(r)) is closely related to PNS activity. In this study, HR was decomposed into HR(r) and the respiration-unrelated component (HR(ru)) based on empirical mode decomposition (EMD) and the relationship between HR and respiration. Time-frequency analysis of HR(r) and HR(ru) was defined as HF(r) and LF(ru), respectively, with specific adaptive bands for every signal. Two experimental data sets, representing SNS and PNS activation, respectively, were used for efficiency analysis of our method. Our results show that the corrected HRV predicted ANS activity well. HF(r) could be an index of PNS activity, LF(ru) mainly reflected SNS activity, and LF(ru)/HF(r) could be more accurate in representing the sympathovagal balance.NEW & NOTEWORTHY This study includes the time-varying relationship between respiration and heart rate in the analysis of heart rate variability. Correction for low-frequency and high-frequency components based on respiration significantly improved evaluation of the sympathetic and parasympathetic nervous systems.