This technology provides a method for estimating confidence intervals for systolic and diastolic blood pressure in oscillometric measurements using cuff pressure oscillations. It determines the two-stage pseudo-maximum amplitude position from the envelope curve using a double non-parametric bootstrap and derives blood pressure confidence intervals by connecting them with bootstrap pseudo-envelopes.
While the maximum amplitude algorithm is widely used for mean arterial pressure estimation, blood pressure fluctuates easily due to stress, exercise, or diet, making it difficult to provide reliable ranges with limited measurements. Single bootstrap methods suffer from high coverage error and wider confidence intervals in impulsive or Gaussian noise environments.
This technology uses a second bootstrap to resample the pseudo-maximum amplitude obtained from the first bootstrap after trimming the mean, and suppresses noise with a weighted average filter to produce narrower, more stable confidence intervals. It can be applied to home and clinical automated blood pressure monitors and remote health monitoring devices, allowing for the quantification of measurement uncertainty even with few readings.
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