Key result
Local nonlinear prediction methods demonstrated that short-term heart period variability at rest is mostly linear, while sympathetic activation decreases complexity and slow breathing increases nonlinearity.
Population
Healthy young subjects
Authors
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May justify linear HRV metrics at rest; leaves open nonlinear dynamics during sympathetic activation or slow breathing.
Short-term heart period variability at rest is mostly linear, but complexity decreases with sympathetic activation and slow breathing, which also increases nonlinear components.
Porta et al. (2006) studied Healthy young subjects. Local nonlinear prediction methods vs. Different types of surrogate data (FT, AAFT, IAAFT-1, IAAFT-2) was evaluated on Complexity and detection of nonlinear dynamics. Local nonlinear prediction methods demonstrated that short-term heart period variability at rest is mostly linear, while sympathetic activation decreases complexity and slow breathing increases nonlinearity.
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