期刊
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
卷 68, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.bspc.2021.102736
关键词
Heart-rate variability; Integral pulse frequency modulation; Sympathovagal modulation; Sympathetic activity; Parasympathetic activity; Brain-heart interplay
资金
- European Commission [813234]
- Italian Ministry of Education and Research (MIUR)
A novel model inspired by IPFM is proposed to accurately predict HRV, outperforming the standard method. By utilizing sympathetic and vagal dynamics for driving, it provides accurate RR interval predictions during resting and postural changes.
Computational models that generate synthetic heart rate variability (HRV) series constitute important tools for the assessment of the effect of autonomic nervous system activity on cardiovascular control, and for the evaluation of novel algorithms using synthetic data. A widely used technique for synthetic HRV generation is the integral pulse frequency modulation (IPFM) model; however, IPFM relies on the HRV spectral paradigm, which cannot separate sympathetic and vagal oscillations that are overlapped in the low-frequency band (0.04-0.15 Hz). To overcome this limitation, a novel IPFM-inspired model driven by cardiac sympathetic and vagal dynamics estimated from HRV is proposed, where our recently developed sympathetic and parasympathetic activity indices that rely on orthonormal Laguerre expansions of the RR interval autoregressive kernels are exploited. The performance of the proposed model is evaluated by comparing the synthetic vs. real RR interval series in a simulation study involving postural changes, with real HRV data gathered from 10 healthy subjects. Moreover, the performance of the proposed model is compared with that of the standard IPFM to discern different autonomic control states associated with resting and postural changes. The results confirm that the proposed physiologically inspired model adequately predicts RR intervals during resting and postural changes. The proposed model clearly outperforms the standard IPFM method, considering both median error, and maximum error. The developed model provides valuable insights for a better understanding of the sympathovagal activity in the analysis of heartbeat dynamics.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据